Hasil untuk "Hydraulic engineering"

L. Yang

ZHANG Yan, HE Jia, ZHANG Xiaofei et al.

【Background and Objective】Topsoil water content is a critical factor influencing crop growth and yield, yet traditional measurement methods are often limited in efficiency and scalability. UAV-based remote sensing provides a promising alternative for rapid, high-resolution in situ measurements. This paper evaluates the factors that affect the accuracy of UAV-based soil water content inversion and identifies the optimal combinations of data types, features, and modelling approaches for improving the accuracy of the UAV-based method.【Method】The experiment was conducted in a maize field during its early growth stage, characterized by substantial variation in canopy coverage. UAV imageries and ground-truth measurements were collected simultaneously. A threshold method was applied to remove the influence of soil background information and calculate vegetation coverage. Spectral and texture features were extracted, and vegetation coverage was integrated into different data combination patterns. Three regression methods: random forest regression, ridge regression and partial least squares regression, were used to construct the inversion model for estimating topsoil water content; comparison of their performance was analyzed under different scenarios.【Result】① The effect of background information removal on model accuracy varied with regression method and the data extracted from sensors. In particular, inversion accuracy improved after soil background information removal for RGB sensors but decreased for TIR sensors. ② The combination of visible and thermal infrared data significantly improved model accuracy, providing richer information and improving robustness. ③ Incorporating vegetation coverage improved accuracy of the predicted topsoil water content both with and without background information removal. For datasets without background information removal, the R2 of the methods using the RGB+TIR+FVC pattern increased by 0.01 compared to that of using the RGB+TIR pattern. After background information removal, their R2 increased by 0.11.【Conclusion】Our results show that different data combinations and inclusion of vegetation coverage had varying effects on the accuracy of UAV-based method for topsoil water content estimation. We screened optimal combinations and methods to increase the accuracy of the method for estimating topsoil water content in the early maize growing stage.

FANG Peng, CHEN Guihua, LI Haifeng

The Qianjiang sub-dam of the Datengxia Water Conservancy Project is a rock-fill dam with clay core, in which the fine-grained filter material between the clay core and the rock in the dam shell is selected from the artificial medium coarse sand produced by the engineering sand and gravel system. Since the quality of the clay core is directly affected by the performance of the filter material and the filling, it is necessary to inspect the performance of the raw material before the filter material filling and conduct filling and rolling tests after passing the inspection. Based on the test results, the optimal rolling parameter combination for artificial medium coarse sand filter material was determined to be a 40 cm layer thickness and 4-time rolling. According to the review test results after construction, the medium coarse sand filter layer constructed under the recommended parameters is qualified. The leakage detection results during the operation of the Qianjiang sub-dam show that there is no abnormal leakage in the dam body.

WEN Shu-jie, XU Chang-yi, HUANG Xiang, HUANG Ying-hao, FU He-lin

[Objective] A method for preparing solidified lightweight red sandstone soil using microbial-induced calcium carbonate precipitation (MICP) technology was proposed for the recycle use of red sandstone residual soil in engineering. A design study was conducted on bio-based solidified lightweight red sandstone soil to investigate the solidification mechanism of the modified material. The effects of expanded polystyrene (EPS) mass content and cementation solution concentration on the strength of the lightweight solidified soil are analyzed. Based on this, the compression failure characteristics of the solidified lightweight red sandstone soil are studied, and its cementation mechanism is validated through both strength analysis and failure characteristics. [Methods] Bacillus pasteurii was selected as the target strain, and cementation solutions with concentrations ranging from 0.5 to 2.0 mol/L were prepared. Solidified lightweight red sandstone soil samples with EPS contents ranging from 0% to 1.125% were prepared. The internal microstructure of the modified red sandstone residual soil was analyzed using X-ray diffraction (XRD) and scanning electron microscopy (SEM). Additionally, its mechanical properties were evaluated through slow shear tests and uniaxial compression tests. [Results] After MICP treatment, a substantial amount of calcite-type CaCO3 precipitates was generated within the red sandstone residual soil. These CaCO3 crystals formed a continuous and dense cementation network between soil particles, serving as the primary contributor to the strength of the solidified lightweight red sandstone soil. In contrast, only sparse crystal clusters were observed on the surfaces of hydrophobic EPS particles. When the cementation solution concentration was 1.5 mol/L and the EPS content was 0.375%, the solidified lightweight red sandstone soil samples exhibited the optimal performance combination. The compressive strength reached 0.76 MPa, meeting the standard requirement (≥0.6 MPa) for foam lightweight soil. The bulk density was 14.3 kN/m3, representing a 13% reduction compared to the undisturbed soil. Additionally, the internal friction angle and cohesion increased by 39% and 17%, respectively. Failure mode analysis revealed that samples with low EPS content (≤0.375%) exhibited typical brittle shear failure, with cracks propagating in a “Y” shape. In contrast, samples with high EPS content (≥1.125%) showed bulging failure, accompanied by surface spalling and debris detachment. [Conclusions] The combination of microbial solidification technology and EPS lightweight foam soil technology has effectively solidified lightweight red sandstone soil, overcoming the high energy consumption limitations of traditional cement-based solidification methods. A quantitative relationship between “cementation solution concentration, EPS content, and mechanical properties” was established. The proposed optimal mix ratio (1.5 mol/L cementation solution + 0.375% EPS) combines both lightweight characteristics (bulk density of 14.3 kN/m3) and high strength (0.76 MPa). This study provides a low-carbon and environmentally friendly solution for the resource utilization of red sandstone residual soil, demonstrating significant application value in engineering fields such as subgrade filling.

Ali Nasiri Khiavi, Mehdi Vafakhah, Dongkun Kim et al.

ABSTRACT This study develops a comprehensive framework for mapping flood susceptibility and vulnerability in the Cheshmeh‐Kileh forest watershed in northern Iran by integrating remote sensing (RS), local knowledge, and machine learning (ML) algorithms. This was accomplished through the application of various MLs, such as K‐nearest neighbor (KNN), random forest (RF), support vector regression (SVR), and Naive Bayes. In this study, flood susceptibility refers to the physical propensity of an area to experience flooding, influenced by geo‐environmental factors, while flood vulnerability captures the socio‐economic and institutional dimensions that determine a community's ability to cope with and recover from flood events. This research first identified critical geo‐environmental factors influencing flood susceptibility and utilized remote sensing to locate areas prone to runoff generation. Flood risk zoning was then implemented using machine learning techniques in Python. To assess flood vulnerability, data were collected from local residents via questionnaires, focusing on economic, infrastructural‐physical, institutional‐policy, and social‐cultural aspects. The flood vulnerability map was created by integrating these survey results with population density data to identify areas where high social exposure coincides with high physical susceptibility. Findings indicated that the combined remote sensing‐SVR model was the most effective for sensitivity classification, identifying sub‐watersheds 2 and 8 in the Sehezar River (a major basin within the study area) as the areas with the highest and lowest flooding susceptibility, respectively, with sub‐watershed 10 in the Dohezar River (another major basin) being the most vulnerable. The estimated values for Mean Absolute Error (0.041), Mean Square Error (0.042), Root Mean Square Error (0.205), and Area Under the Curve (0.980) demonstrated high model accuracy. The Friedman statistical test showed that the average scores for the different dimensions of vulnerability decreased in the order of: economic (0.48), social‐cultural (0.44), infrastructural‐physical (0.34), and institutional‐policy (0.28). Consequently, the economic dimension was prioritized for its highest score. Flood vulnerability mapping revealed that sub‐watersheds 5, 11, 14, and 15, which had higher population densities, were naturally more vulnerable to floods. This finding reflects a direct relationship between population density and flood vulnerability. Overall, this study underscores the urgent need for effective planning and preventive strategies to mitigate flood risks and enhance resilience in the region.

Hashini Gunatilake, John Grundy, Rashina Hoda et al.

Empathy, defined as the ability to understand and share others' perspectives and emotions, is essential in software engineering (SE), where developers often collaborate with diverse stakeholders. It is also considered as a vital competency in many professional fields such as medicine, healthcare, nursing, animal science, education, marketing, and project management. Despite its importance, empathy remains under-researched in SE. To further explore this, we conducted a socio-technical grounded theory (STGT) study through in-depth semi-structured interviews with 22 software developers and stakeholders. Our study explored the role of empathy in SE and how SE activities and processes can be improved by considering empathy. Through applying the systematic steps of STGT data analysis and theory development, we developed a theory that explains the role of empathy in SE. Our theory details the contexts in which empathy arises, the conditions that shape it, the causes and consequences of its presence and absence. We also identified contingencies for enhancing empathy or overcoming barriers to its expression. Our findings provide practical implications for SE practitioners and researchers, offering a deeper understanding of how to effectively integrate empathy into SE processes.

Y. Navidtehrani, C. Betegón, J. Vallejos et al.

Recent years have seen a significant interest in using phase field approaches to model hydraulic fracture, so as to optimise a process that is key to industries such as petroleum engineering, mining and geothermal energy extraction. Here, we present a novel theoretical and computational phase field framework to simulate hydraulic fracture. The framework is general and versatile, in that it allows for improved treatments of the coupling between fluid flow and the phase field, and encompasses a universal description of the fracture driving force. Among others, this allows us to bring two innovations to the phase field hydraulic fracture community: (i) a new hybrid coupling approach to handle the fracture-fluid flow interplay, offering enhanced accuracy and flexibility; and (ii) a Drucker-Prager-based strain energy decomposition, extending the simulation of hydraulic fracture to materials exhibiting asymmetric tension-compression fracture behaviour (such as shale rocks) and enabling the prediction of geomechanical phenomena such as fault reactivation and stick-slip behaviour. Four case studies are addressed to illustrate these additional modelling capabilities and bring insight into permeability coupling, cracking behaviour, and multiaxial conditions in hydraulic fracturing simulations. The codes developed are made freely available to the community and can be downloaded from {https://mechmat.web.ox.ac.uk/

Roberto Verdecchia, Justus Bogner

From its first adoption in the late 80s, qualitative research has slowly but steadily made a name for itself in what was, and perhaps still is, the predominantly quantitative software engineering (SE) research landscape. As part of our regular column on empirical software engineering (ACM SIGSOFT SEN-ESE), we reflect on the state of qualitative SE research with a focus group of experts. Among other things, we discuss why qualitative SE research is important, how it evolved over time, common impediments faced while practicing it today, and what the future of qualitative SE research might look like. Joining the conversation are Rashina Hoda (Monash University, Australia), Carolyn Seaman (University of Maryland, United States), and Klaas Stol (University College Cork, Ireland). The content of this paper is a faithful account of our conversation from October 25, 2025, which we moderated and edited for our column.

Dipin Khati, Yijin Liu, David N. Palacio et al.

Applications of Large Language Models (LLMs) are rapidly growing in industry and academia for various software engineering (SE) tasks. As these models become more integral to critical processes, ensuring their reliability and trustworthiness becomes essential. Consequently, the concept of trust in these systems is becoming increasingly critical. Well-calibrated trust is important, as excessive trust can lead to security vulnerabilities, and risks, while insufficient trust can hinder innovation. However, the landscape of trust-related concepts in LLMs in SE is relatively unclear, with concepts such as trust, distrust, and trustworthiness lacking clear conceptualizations in the SE community. To bring clarity to the current research status and identify opportunities for future work, we conducted a comprehensive review of $88$ papers: a systematic literature review of $18$ papers focused on LLMs in SE, complemented by an analysis of 70 papers from broader trust literature. Additionally, we conducted a survey study with 25 domain experts to gain insights into practitioners' understanding of trust and identify gaps between existing literature and developers' perceptions. The result of our analysis serves as a roadmap that covers trust-related concepts in LLMs in SE and highlights areas for future exploration.

Ashish Kumar, Sarada Prasad Pradhan, Siddhant Singh et al.

This paper examines the stability of rock slopes along the broad gauge (BG) line near Darekasa (approximately 1.0 km from Darekasa Station towards the western side). Unsafe slopes and rockfalls can hinder train travel, causing commuters difficulties. A field survey and lab experiments determined the rock slope’s stabilizing factors. Kinematic analysis and finite element modeling evaluated slope stability and design. On-site joint orientations were estimated with a Brunton compass (Nautical Mart Inc., Roorkee, India). Stereonet plots show wedge and planar failure patterns. The RS2 software was used to generate a finite element model for critical slope sections utilizing the combined continuum interface method and to determine critical shear strength reduction factors (SSRFs) with a two-dimensional plain strain method. The stabilization of the subject area was evaluated based on these findings. The purpose of rockfall protection is to prevent the fall of any individual blocks caused by the creation of local wedges. During numerical calculations for the global stability of a slope, these types of failures are not detectable. Along the stretch, this scenario demands drapery/rockfall netting. To preserve the slope against instability and rockfall, corrective measures consisting of reinforced double-twisted hexagonal mesh, rhomboidal cable net, and self-drilling anchors were implemented.

Kurella Bhanu Revathi, Mimansa, Mankani Aishwarya et al.

Heavy metals cause alarming levels of environmental and health problems and among them Cadmium has become a threat to organisms and natural resources like soil and water alike. It accumulates in living systems thereby causing oxidative stress. Efforts are made for bioremediation of heavy metals by employing biosorption, which is a well-known economic method for removal and in the current study Selaginella bryopteris was used as biosorbent. The biosorption capacity was optimized by its physicochemical parameters such as pH, dosage, contact time, and temperature. Cadmium-induced Reactive Oxygen Species levels and the antioxidant potential of S. bryopteris in ameliorating them were studied in Drosophila melanogaster. Water-quality analysis was performed using Chemical Oxygen Demand(COD) and Biological Oxygen Demand (BOD) and effect of S.bryopteris on these parameters were also analyzed. Further the concentration of Cadmium via colorimetric assay and Atomic Absorption Spectroscopy(AAS) was employed to quantify the Cadmium in lake water samples before and after treatment with biosorbent. Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM) were performed to characterize the surface properties for adsorptive removal of metal ions, and antioxidant studies were conducted to assess the role of S. bryopteris in suppressing oxidative stress.

LIU Jin, CHEN Yechao, DING Wu et al.

The river system in the Pearl River Delta river network is complex with numerous embankments, among which the Zhongshun Dawei river system has the most complex structure and the greatest difficulty in the joint dispatching of sluices and pumps. In order to fully explore the potential of joint dispatching of water projects in controlling water quantity and quality, this paper took Zhongshun Dawei as the research object, constructed a one-dimensional hydrodynamic-water quality coupling model for Zhongshun Dawei, and simulated water quantity and quality processes within the embankment under various dispatching schemes of sluices and pumps. On this basis, a joint optimization dispatching model for sluices and pumps was established to achieve the optimal decision-making of dispatching schemes under different water diversion conditions. Finally, based on the simulation and dispatching models of water quantity and quality, a water quantity and quality dispatching simulation system for the Zhongshun Dawei river network was developed, which realized the simulation of hydrodynamic characteristics of Zhongshun Dawei, the dynamic simulation of pollutant concentration and water quality changes, the emergency dispatching of water pollution, and the visualization of the process. A water quantity and quality simulation and control technology system based on joint optimization dispatching of sluices and pumps under the connection of the Zhongshun Dawei river system was formed. Based on the system, two typical scenarios were analyzed, and the results show that in the case of optimization dispatching, the weighted concentrations of COD and NH3-N at the end of the dispatching period are improved by 10.26% and 27.27%, respectively, compared with the case without optimization dispatching. These findings demonstrate the significant dispatching effects and provide reliable technical support for water quantity and quality dispatching decision-making in the Zhongshun Dawei region.

Boyi CONG, Yang LIU, Haoxiang YIN et al.

Coal chemical wastewater exhibits complex water quality, with a high concentration of difficult-to-degrade organic matter and ammonia nitrogen, posing significant challenges for wastewater treatment. Current technologies, including coagulation, adsorption, and membrane bioreactors, have limitations such as high costs, unstable operation, and suboptimal pretreatment effects, failing to meet the evolving needs of the coal chemical industry. This study introduces a novel method using the reducibility of phenolic organic compounds in coal chemical wastewater to enhance the Fe³⁺/Fe²⁺ cycle in the Fe³⁺/H₂O₂ Fenton-like system, thus efficiently treating the wastewater. Comparative experiments demonstrated that the Fe³⁺/H₂O₂ system achieves removal rates of COD, TOC, TN, and NH₃–N at 74.63%, 52.62%, 10.46%, and 15.11%, respectively. This system significantly reduces coloration, shows the largest decline in the UV-Vis spectrum, and decreases the amount of iron sludge. Q-TOF analysis revealed that the primary eight organic compounds in the wastewater are phenolic or contain reducible functional groups such as aldehyde, carbonyl, carboxyl, carbon-carbon double bond, or ester. By monitoring changes in the COD removal rate and pH, Fe³⁺/Fe²⁺, H₂O₂, and others over time, the mechanism of organic matter removal in the Fe³⁺/H₂O₂ system is proposed: the reducible organic matter reduces Fe³⁺ to Fe²⁺, enhancing the Fe³⁺/Fe²⁺ cycle, and the generated Fe²⁺ reacts with H₂O₂ to remove organic pollutants via the Fenton reaction. Optimal operating conditions are identified as Fe₂(SO₄)₃ dosage of 1.0 g/L, H₂O₂ dosage of 50 mol/L, reaction temperature of 30 °C, and initial pH of 6.8 using the controlled variable method. Under these conditions, after 60 minutes, the treatment shows significant COD, TOC, TN, and NH₃–N removal efficiencies, a significant reduction in color, and an increase in biodegradability, with the B/C ratio rising from 0.17 to 0.47. This study confirms the viability of using a self-reduction Fe³⁺/H₂O₂ system for phenolic coal chemical wastewater, reducing operating costs and providing a theoretical foundation for further research and engineering applications.

Ebube Alor, Ahmad Abdellatif, SayedHassan Khatoonabadi et al.

Software engineering (SE) chatbots are increasingly gaining attention for their role in enhancing development processes. At the core of chatbots are Natural Language Understanding platforms (NLUs), which enable them to comprehend user queries but require labeled data for training. However, acquiring such labeled data for SE chatbots is challenging due to the scarcity of high-quality datasets, as training requires specialized vocabulary and phrases not found in typical language datasets. Consequently, developers often resort to manually annotating user queries -- a time-consuming and resource-intensive process. Previous approaches require human intervention to generate rules, called labeling functions (LFs), that categorize queries based on specific patterns. To address this issue, we propose an approach to automatically generate LFs by extracting patterns from labeled user queries. We evaluate our approach on four SE datasets and measure performance improvement from training NLUs on queries labeled by the generated LFs. The generated LFs effectively label data with AUC scores up to 85.3% and NLU performance improvements up to 27.2%. Furthermore, our results show that the number of LFs affects labeling performance. We believe that our approach can save time and resources in labeling users' queries, allowing practitioners to focus on core chatbot functionalities rather than manually labeling queries.

Chengzeng Yan, Hong Zheng, Guanhua Sun et al.

M. Behdarnejad, H. Piri, M. Delbari

Introduction In sustainable farming systems, the use of organic fertilizers is of particular importance in increasing crop production and maintaining sustainable soil fertility. Nowadays, the consumption of organic foods is introduced to consumers as an alternative. The result of the application of chemical products is the crisis of environmental pollution, soil and water resources, and the health risk to human society. Nowadays, in order to reduce the effects of misuse of chemical inputs, chemical fertilizers can be replaced with organic biological fertilizers, including animal manure, compost, and green manure. In this regard, chicken manure has a positive effect on the physical, chemical, and biological characteristics of the soil, and due to its richness in uric acid, the nitrogen contained in it is used by the plant much faster than the nitrogen of other organic fertilizers. Vermicompost is considered a good source of soil fertility due to its organic materials. Organic matter in the soil improves the permeability and drainage of the soil and also prevents excessive dryness of the soil by maintaining sufficient moisture. Despite the fact that vermicompost can be used as a fertilizer in organic farming, high levels of this fertilizer may cause salinity effects in the plant, which affects the growth and development of the plant and even it can cause the death of cucumber as one of the crops sensitive to soil and water salinity. The cucumber (Cucumis sativus L.) is one of the important vegetables that can be produced in a greenhouse all year round. Fresh consumption of cucumber throughout the year has increased its production. The development of technology and the short growth period of this product has made it possible to grow it in most climate zones. Therefore, in this research, the effects of different levels of water deficit with the simultaneous application of vermicompost and chicken manure on cucumber plants in the Behbahan region have been investigated. Materials and Methods In this study, different levels of irrigation water, vermicompost, and poultry manure on ground cucumber were investigated. The experiment was performed in the form of split plots based on completely randomized design and the form of stacks. Treatments included three levels of poultry manure (2, 4 and 8 ton ha-1), three levels of vermicompost (3, 6 and 9 ton ha-1) and three levels of water stress (100, 75 and 50% of plant water requirement). Both vermicompost and poultry manure were applied to the soil before planting. Harvest was done every three days. Fruit weight, diameter and length, plant length, the protein of the dry matter of the fruit percentage, and leaf chlorophyll in each plot were carefully measured. Also, the yield and water productivity at the end of the season were calculated. Water productivity  Referring to the yield to irrigation water ratio, is obtained by the following relation (Payero et al., 2009): WP=Y/IR                                                                                                                               (1) In this equation, WP represents water productivity (kg/m3), Y denotes the yield (kg/ha), and IR shows the amount of irrigation water (m3/ha). Statistical analysis The analysis of variance for the results obtained from different treatments was conducted using SAS software (SAS 9.1, SAS Institute, Cary, NC, USA). The mean values of the main factors and interactive effects were compared using the Duncan method at the 1% and 5% levels of significance. Results and Discussion The results showed that irrigation, poultry manure and vermicompost had a significant effect on the measured parameters at the level of one and five percent probability. Reduction of water consumption reduced yield and yield components, but in this regard, no significant difference was observed between 100% and 75% of water requirement. The highest yield was obtained in the treatment of 100% of plant water requirement and consumption of 4 ton ha-1 of poultry manure and 6 ton ha-1 of vermicompost, in this regard, no significant difference was observed with the treatment of 75% of water requirement. According to the results obtained from this study, it can be said that there is no significant difference in terms of yield between treatments of 75 and 100% of plant water requirement. Therefore, the amount of water given to the plant can be reduced to 75% of the plant water requirement, and with proper management, less water can be consumed without a significant reduction in crop yield. Examining the effects of irrigation water on the amount of the protein of the dry matter of the fruit showed that the highest amount of the protein of the dry matter of the fruit (56.31%) was obtained in the treatment of 75% of the water requirement and the protein of the dry matter of the fruit was less in other treatments. The interaction effect of vermicompost and poultry manure resulted in the highest percentage of cucumber protein at a treatment of 4 tons ha-1 of poultry manure and 6 tons ha-1 of vermicompost (58.42%). However, when the simultaneous use of 8 tons ha-1 of poultry manure and different levels of vermicompost was employed, the percentage of protein in the fruit's dry matter decreased. The combination of drought stress, poultry manure, and vermicompost, along with their interaction effects, significantly influenced the chlorophyll a and b values at both the 1% and 5% probability levels. As the depth of irrigation water decreased, the amounts of chlorophyll a and b also decreased. The treatment with 100% water requirement of the plant showed the highest amounts of chlorophyll a (0.63 mg/g fresh weight) and chlorophyll b (0.36 mg/g fresh weight). However, no significant difference was observed compared to the 75% treatment. Regarding the interactions between vermicompost and poultry manure, it was found that when using 6 tons ha-1 of vermicompost to reduce yield and its components, the use of poultry manure should be reduced to 4 tons ha-1. On the other hand, when higher levels of vermicompost (9 tons ha-1) are used, the application of poultry manure should be reduced to 2 tons ha-1. Result According to the results obtained from this research, it can be said that there is no significant difference in performance between the treatments of providing 75% and 100% of the water requirement of the plant, therefore, the amount of water given to the plant can be reduced to the amount of 75% of the water requirement of the plant. With proper management, less water can be consumed without significantly reducing the yield of the product.

Li Wei, Li Wei, Xiaopeng Liu et al.

The human-water system synergy in Northwest China has become more significant as the ecological civilization construction continues and the implementation of the 2030 Agenda for Sustainable Development in China proceeds. In this study, taking the Ningxia Hui Autonomous Region as a typical research region, the human–water system coevolution model was established by coupling SD (System Dynamics) model and coevolution model from the theoretical perspective of complex system synergies, to simulate the human-water system’s coevolution trends from 2010 to 2030 in this region. Five regulation schemes were then designed to enhance the synergy of the human-water system by adjusting sensitive decision variables. The results revealed that the supply to demand ratio of water and the synergy index of the human-water system obtained by the status continuation scheme would decline from 1.02 and 0.39 in 2020 to 0.81 and 0.35 in 2030, respectively, indicating the growing gap between water supply and demand and revealing the worsening human-water relationship. Under the comprehensive optimization scheme, the supply to demand ratio of water and the synergy index of the human-water system would be higher than under the other schemes, demonstrating a substantially improved human-water relationship. Hence, a comprehensive optimization regulation scheme is proposed. This scheme combines improving pro-environmental water consumption, adapting industrial structures, and carrying out water conservation and pollution prevention. This research renders a decision-making basis for regulating regional water resources and finding paths to developing a harmonious relationship between humans and water.

Lvyang Yang, Jiankang Zhang, Huaiqiang Li et al.

The digitization of engineering drawings is crucial for efficient reuse, distribution, and archiving. Existing computer vision approaches for digitizing engineering drawings typically assume the input drawings have high quality. However, in reality, engineering drawings are often blurred and distorted due to improper scanning, storage, and transmission, which may jeopardize the effectiveness of existing approaches. This paper focuses on restoring and recognizing low-quality engineering drawings, where an end-to-end framework is proposed to improve the quality of the drawings and identify the graphical symbols on them. The framework uses K-means clustering to classify different engineering drawing patches into simple and complex texture patches based on their gray level co-occurrence matrix statistics. Computer vision operations and a modified Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) model are then used to improve the quality of the two types of patches, respectively. A modified Faster Region-based Convolutional Neural Network (Faster R-CNN) model is used to recognize the quality-enhanced graphical symbols. Additionally, a multi-stage task-driven collaborative learning strategy is proposed to train the modified ESRGAN and Faster R-CNN models to improve the resolution of engineering drawings in the direction that facilitates graphical symbol recognition, rather than human visual perception. A synthetic data generation method is also proposed to construct quality-degraded samples for training the framework. Experiments on real-world electrical diagrams show that the proposed framework achieves an accuracy of 98.98% and a recall of 99.33%, demonstrating its superiority over previous approaches. Moreover, the framework is integrated into a widely-used power system software application to showcase its practicality.

Elizabeth Bjarnason, Mirko Morandini, Markus Borg et al.

The RET (Requirements Engineering and Testing) workshop series provides a meeting point for researchers and practitioners from the two separate fields of Requirements Engineering (RE) and Testing. The goal is to improve the connection and alignment of these two areas through an exchange of ideas, challenges, practices, experiences and results. The long term aim is to build a community and a body of knowledge within the intersection of RE and Testing, i.e. RET. The 2nd workshop was held in co-location with ICSE 2015 in Florence, Italy. The workshop continued in the same interactive vein as the 1st one and included a keynote, paper presentations with ample time for discussions, and a group exercise. For true impact and relevance this cross-cutting area requires contribution from both RE and Testing, and from both researchers and practitioners. A range of papers were presented from short experience papers to full research papers that cover connections between the two fields. One of the main outputs of the 2nd workshop was a categorization of the presented workshop papers according to an initial definition of the area of RET which identifies the aspects RE, Testing and coordination effect.

Mphatso Malota, Joshua Mchenga, Brighton Austin Chunga

Abstract The agricultural drainage engineering community is steadily shifting the design of subsurface drainage systems from the experience-based design approach to the simulation-based design approach. As with any design problem, two challenges are faced; firstly, how to determine all the input data required by the simulation model, and secondly to, a priori, anticipate what the performance of the designed system will be. This study sought to evaluate the performance of the WaSim model to simulate fluctuating water table depths (WTD), and drainage discharges (DD) in KwaZulu-Natal Province, South Africa. Saturated hydraulic conductivity (K sat), which is an input to the WaSim model, was estimated by the Rosetta computer program, based on soil particle size distribution data, bulk density, and soil water retention characteristics at pressure heads of – 33 and – 1500 kPa. performance of the WaSim model was statistically assessed using the coefficient of determination (R 2), coefficient of residual mass (CRM), mean absolute error (MAE), mean percent error (MPE), and the nash–sutcliffe efficiency (NSE). during the validation period, the WaSim model predicted WTDs with R 2, CRM, MAE, MPE, and NSE of 0.86, 0.003, 4.9 cm, 6.0%, and 0.98, respectively. In the same validation period, the model predicted DDs with R 2, CRM, MAE, MPE, and NSE of 0.57, 0.002, 0.30 mm day−1,11%, and 0.76, respectively. These results suggest that the use of Rosetta-estimated K sat data as inputs to the WaSim model compromised its accuracy and applicability as a subsurface drainage design tool. Owing to the relatively low R 2 value of 0.57, and that the WaSim model was empirically developed, we recommend further improvement on the calibration of the model for it to be suitable for application under the prevailing conditions. Also, in the absence of other means of determining K sat, we caution the use of Rosetta-estimated K sat data as inputs to the WaSim model for the design and analysis of subsurface drainage systems in KwaZulu-Natal Province, South Africa.