Hasil untuk "Irrigation engineering. Reclamation of wasteland. Drainage"

Paloma Guenes, Rafael Tomaz, Maria Teresa Baldassarre et al.

The Impostor Phenomenon (IP) impacts a significant portion of the Software Engineering workforce, yet it is often viewed primarily through an internal individual lens. In this position paper, we propose framing the prevalence of IP as a form of Human Debt and discuss the relation with the ICSE2026 Pre Survey on the Future of Software Engineering results. Similar to technical debt, which arises when short-term goals are prioritized over long-term structural integrity, Human Debt accumulates due to gaps in psychological safety and inclusive support within socio-technical ecosystems. We observe that this debt is not distributed equally, it weighs heavier on underrepresented engineers and researchers, who face compounded challenges within traditional hierarchical structures and academic environments. We propose cultural refactoring, transparency and active maintenance through allyship, suggesting that leaders and institutions must address the environmental factors that exacerbate these feelings, ensuring a sustainable ecosystem for all professionals.

LIU Yang, XU Jing, GUAN Xiaoyan et al.

【Background and Objective】Soil salinity is a common challenge for crop production in Northwestern China, and various engineering and agronomic methods have been developed to alleviate or reclaim saline-alkali soils. This paper reviews the advantages and disadvantages of drainage engineering methods, including open ditches, buried drains, and boreholes, for treating saline-alkali soils in Ningxia Province. It proposes the most effective drainage methods for saline-alkali soils in different regions, aiming to provide protocols for improving soil management in the province.【Method】This review focuses on work conducted in regions such as Huinong District and Pingluo County in Shizuishan City, Helan County and Xingqing District in Yinchuan City, and Hongsipu District in Wuzhong City. Literature and engineering data were collected from various sources to analyze and identify the appropriate drainage methods for each region. The VOSviewer was used to analyze and summarize key research topics related to drainage engineering methods for reclaiming saline-alkali soils in the province. 【Result】①The primary drainage systems for saline-alkali soils in the province include open ditches, supplemented by buried drains and pumping boreholes. Maintenance of these systems should be strengthened to improve their effectiveness and operational efficiency. ② In Huinong District and Pingluo County, located in low-lying areas near lakes and wetlands, the soil has low permeability, and buried drains and pumping boreholes are the most appropriate methods to maintain the groundwater table below a critical depth. In areas with clayey soils, combining these methods with soil barrier removal would enhance efficiency. ③ In Helan County and Xingqing District (Yinchuan City), the cultivated saline-alkali soils require drainage ditch maintenance and protection. A combination of boreholes and buried drains should be considered based on local conditions. ④ In Hongsipu District (Wuzhong City), topsoil salinity can be reduced by leaching using ditch drainage, while salinity in the subsoil can be managed with buried drains or leaching using borehole pumping. 【Conclusion】 Drainage engineering practices are critical for reclaiming saline-alkali lands in Ningxia Province. Selecting an appropriate drainage method based on regional characteristics is essential to improving reclamation efficiency. Future research should focus on combining engineering, biological, chemical, and physical methods to better manage saline-alkali soils in the province.

TIAN Wenhui, LIU Jiabin, GAO Xiaodong et al.

【Objective】Fertigation is a key technique for ensuring sustained yield and resource use efficiency of orchards and has become a global research focus. This paper provides a systematic overview on the current status, research hotspots and emerging trends in orchard fertigation.【Method】Literature from the China National Knowledge Infrastructure (CNKI) and Web of Science (WOS) databases was analyzed using VOSviewer and CiteSpace for visualization. The analysis focused on the number of publications, lead institutions, contributing countries, and frequently used keywords in orchard fertigation.【Result】The number of publications in both Chinese and English journals has shown a steady increase, with horticultural journals publishing the most articles. However, the number of publications and the level of collaboration among Chinese institutions and authors remain relatively low. Among the top ten most productive institutions in English journals, two are from China and four from the United States. The United States leads in terms of number of publication, total citations, and H-index. Regarding international collaboration, the United States is at the top of the ranking, followed by China. Research areas in papers published in Chinese journals have evolved from evaluating technical applications to innovating technologies aimed at achieving precision irrigation and fertilization, with water-saving and digitalization emerging as top research areas. In contrast, research areas in English journals have shifted from soil fertility to water use efficiency, and current hotspots include gas exchange and nitrogen absorption and distribution. Additionally, there is growing emphasis on protecting ecological functions and minimizing environmental impact in the use of fertigation.【Conclusion】Orchard fertigation remains a prominent research hotspot. Future advancements in fertigation technology are expected to move toward more scientific, intelligent, automated, and precision control.

Sh. Asghari, K. Heidari, M. Hasanpour Kashani et al.

Introduction  The study of soil mean weight diameter (MWD) of wet aggregates that is important for sustainable soil management, has recently received much attention. As the prediction of MWD is challenging, laborious, and time-consuming, there is a crucial need to develop a predictive estimation method to generate helpful information required for the soil health assessment to save time and cost involved in soil analysis. Therefore, it is useful to use different models such as multiple linear regression (MLR) and intelligent models including artificial neural network (ANN) and gene expression programming (GEP) to estimate MWD of wet aggregates through easily accessible and low-cost soil properties. The objectives of this study were (1) to creating MLR, ANN and GEP models for predicting MWD from the easily measurable soil variables in forest, range and cultivated lands of the Fandoghloo region of Ardabil province, (2) to compare the precision of the mentioned models in the prediction of MWD of wet aggregates using the coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) criteria.   Materials and Methods  Disturbed and undisturbed soil samples (n= 80) were nearly systematically taken from 0-10 cm depth with nearly 50 m distance in forest (n= 20), range (n= 23) and cultivated (n= 37) lands of the Fandoghloo region of Ardabil province, Iran (lat. 38° 24' 10" to 38° 24' 25" N, long. 48° 32' 45" to 48° 33' 5" E) in summer 2023. The contents of sand, silt, clay, CaCO3, pH, EC, bulk (BD) and particle (PD) density, organic carbon (OC), geometric mean diameter (GMD) of dry aggregates were determined in the laboratory using standard methods. Total porosity (n) was calculated using BD and PD data (n= 1-BD/PD). The mean geometric diameter (dg) and geometric standard deviation (σg) of soil particles were computed by sand, silt and clay percentages. The mean weight diameter (MWD) of wet aggregates was measured in the aggregates smaller than 4.75 mm by wet sieving equipment using sieves with 2, 1, 0.5, 0.25 and 0.106 mm pore diameter. All data were randomly divided into two series as 60 data for training and 20 data for testing of models. The SPSS 22 software with the stepwise method, MATLAB and Gene Xpro Tools 4.0 software were used to derive multiple linear regression (MLR), artificial neural network (ANN) and gene expression programming (GEP) models, respectively. A feed forward three-layer (9, 8, 6 and 6 neurons in the hidden layer) perceptron network and the tangent sigmoid transfer function were used for the ANN modeling. A set of optimal parameters were chosen before developing the best GEP model. The number of chromosomes and genes, head size and linking function were selected by the trial and error method, and they are 30, 3, 8, and +, respectively. The rates of genetic operators were chosen according to literature studies. The precision of MLR, ANN and GEP models in predicting MWD of wet aggregates were evaluated by the coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) statistics.   Results and Discussion The values of sand (13.14 to 64.79 %), silt (21.11 to 74.96 %), clay (3 to 42.18 %), OC (1.01 to 7.17 %), PD (2.00 to 2.67 g cm-3), n (0.39 to 0.87 cm3 cm-3), GMD of dry aggregates (0.8 to 1.33 mm) and MWD of wet aggregates (0.35 to 2.65 mm) showed good variations in the soils of the studied region. The studied soils had clay loam (n= 11), sandy clay loam (n= 6), sandy loam (n= 12), loam (n= 13), silty clay loam (n= 14), silty clay (n= 1) and silt loam (n= 23) textural classes. There were found significant correlations between MWD with OC (r= 0.67**), sand (r= 0.70**), GMD (r= 0.30**) and PD (r= -0.46**). Also, significant and positive correlation was found between OC and sand (r= 0.59**). Due to the multicollinearity of sand with dg (r= 0.87**), we did not use the dg as an input variable to estimate MWD of wet aggregates. Generally, four MLR, ANN and GEP models were constructed to predict MWD of wet aggregates from measured readily available soil variables. The results of MLR, ANN and GEP models indicated that the most suitable variables to estimate MWD of wet aggregates were sand, OC and GMD of dry aggregates. The values of R2, RMSE, ME and NS criteria were obtained equal 0.52, 0.48 mm, 0.13 mm and 0.48, and 0.85, 0.30 mm, 0.03 mm and 0.78, 0.79, 0.35 mm, -0.10 mm, 0.95 for the best MLR, ANN and GEP models in the testing data set, respectively. Many researchers also reported that there is a positive and significant correlation between MWD of wet aggregates and OC.   Conclusion  The results showed that sand, OC and GMD of dry aggregates were the most important and readily available soil variables to predict the mean weight diameter (MWD) of wet aggregates in the Fandoghloo region of Ardabil province. According to the lowest values of RMSE and the highest values of R2 and NS, the precision of ANN models to predict MWD of wet aggregates was more than MLR and GEP models in this study. Because ANN is more flexible and effectively captures non-linear relationships, it performed better than the other models in predicting MWD.

Marvin Wyrich, Lloyd Montgomery

A well-rounded software engineer is often defined by technical prowess and the ability to deliver on complex projects. However, the narrative around the ideal Software Engineering (SE) candidate is evolving, suggesting that there is more to the story. This article explores the non-technical aspects emphasized in SE job postings, revealing the sociotechnical and organizational expectations of employers. Our Thematic Analysis of 100 job postings shows that employers seek candidates who align with their sense of purpose, fit within company culture, pursue personal and career growth, and excel in interpersonal interactions. This study contributes to ongoing discussions in the SE community about the evolving role and workplace context of software engineers beyond technical skills. By highlighting these expectations, we provide relevant insights for researchers, educators, practitioners, and recruiters. Additionally, our analysis offers a valuable snapshot of SE job postings in 2023, providing a scientific record of prevailing trends and expectations.

Matthew Okner, David Veksler

This paper presents the design and implementation of an automated water irrigation system aimed at optimizing plant care through precision moisture monitoring and controlled water delivery. The system uses a capacitive soil moisture sensor, an ADC (analog-to-digital converter), and a relay-driven water pump to ensure plants receive adequate hydration based on real-time data. In addition, this work aims to build on existing applications for Raspberry Pi (4B) and Arduino-based automatic irrigation systems by integrating advanced calibration methods, employing optimized algorithms, and introducing new technologies to further enhance overall system efficiency and reliability.

Yunus Emre Kunt

Agricultural irrigation ensures that the water required for plant growth is delivered to the soil in a controlled manner. However, uncontrolled management can lead to water waste while reducing agricultural productivity. Drip irrigation systems, which have been one of the most efficient methods since the 1970s, are modernised with IoT and artificial intelligence in this study, aiming to both increase efficiency and prevent water waste. The developed system is designed to be applicable to different agricultural production areas and tested with a prototype consisting of 3 rows and 3 columns. The project will commence with the transmission of environmental data from the ESP32 microcontroller to a computer via USB connection, where it will be processed using an LSTM model to perform learning and prediction. The user will be able to control the system manually or delegate it to artificial intelligence through the Blynk application. The system includes ESP32 microcontroller, rain and soil moisture sensors, DHT11 temperature and humidity sensor, relays, solenoid valves and 12V power supply. The system aims to increase labour productivity and contribute to the conservation of water resources by enabling agricultural and greenhouse workers to focus on processes other than irrigation. In addition, the developed autonomous irrigation system will support the spread of sustainable agricultural practices and increase agricultural productivity. Keywords: Autonomous Irrigation, IoT, Artificial Intelligence, Agriculture, Water Management

Elżbieta Radzka, Katarzyna Rymuza

The purpose of the work is to characterise pluvial conditions in central-eastern Poland from the beginning of the 21 st century (2001–2020). The analysis involved seven meteorological stations of the Institute of Meteorology and Water Management – National Research Institute (IMGW-PIB): Białowieża, Legionowo, Pułtusk, Siedlce, Szepietowo, Terespol and Warsaw. The work contains the analysis of the annual and seasonal atmospheric precipitation pattern (summer, winter, spring and autumn) and its temporal and spatial variation throughout a 20-year period. Moreover, the percentage share of precipitation in each season in the annual sum was calculated. In order to analyse precipitation patterns in the study period, the Innovative Trend Analysis (ITA) was applied. The average long-term annual atmospheric precipitation sum ranged from 557 mm at Terespol to 653 mm at Białowieża. The highest seasonal precipitation sum in the studied region was recorded for the summer (218 mm) whereas in spring and autumn, precipitation stayed at a similar level and amounted to 130 and 131 mm, respectively. The lowest precipitation was recorded in winter (109 mm). The highest percentage share of the atmospheric precipitation sum was associated with summer rainfall (from 35 to 38%), whereas the lowest in winter (from 18 to 20%). Comparisons of 2001–2010 and 2011–2020 decades revealed a decline in the share of summer precipitation in the annual sum at most of the stations, and an increase in the share of winter precipitation. The ITA demonstrated that the most significant trends in precipitation change occurred in summer and winter and the directions of the trends were different for each station.

احمد آغشلوئی, مجتبی شوریان, امیر علیزاده فرد

در راستای مدیریت کارآمد حوضه آبریز، بررسی رویداد حدی سیل به‌دلیل فراوانی بالا و ایجاد خسارت‌های جانی و مالی اهمیت ویژه­ای دارد. از طرفی با توجه‌ به بحران آبی و مدیریت سیلاب در مصارف کشاورزی، بررسی سیل امری ضروری است، بنابراین در این پژوهش به برآورد حداکثر سیلاب محتمل (PMF) حوضه آبریز سد لتیان با استفاده از تئوری بیزین و مدل HEC-HMS پرداخته شده است. در این راستا در گام نخست، بیش‌ترین بارش محتمل (PMP) حوضه آبریز با به‌کارگیری آمار 70 ساله محاسبه شده است. سپس با استفاده از تئوری بیزین، به‌عنوان مدلی تصادفی، حداکثر سیلاب حوضه با بررسی پنج مقدار گسسته ضریب تغییرات و چهار سناریوی دبی حداکثر سالیانه، حداکثر فراز روزانه، حداکثر سالیانه و لحظه‌ای، حداکثر فراز روزانه و لحظه‌ای تعیین شد. در گام دوم پژوهش نیز مدل HEC-HMS حوضه آبریز سد لتیان ایجادشده و با اعمال PMP محاسبه‌شده، PMF حوضه تعیین شد. پس از بررسی نتایج با توجه به مقادیر خطا، ضریب تغییرات 4/0 درنظر گرفته شد و دو سناریو حداکثر فراز روزانه و حداکثر فراز روزانه با سیلاب لحظه­ای به‌عنوان سناریوهای منتخب انتخاب شدند که میانگین برآورد پسین آن­ها به‌ترتیب 1532 و 1577 مترمکعب بر ثانیه می باشد. نتایج مدل HEC-HMS نیز حاکی از آن است که مقدار PMF حوضه آبریز سد لتیان 1025 متر­مکعب بر ثانیه می­باشد که 34 درصد کم‌تر از مقدار محاسبه‌شده با استفاده از تئوری بیزین است. براساس نتایج با توجه به داده­های موجود در منطقه موردمطالعه، استفاده از تئوری بیزین نتایج بهتری ارائه می­دهد.

Bernard T. Agyeman, Jinfeng Liu, Sirish L. Shah

Efficient water management in agriculture is important for mitigating the growing freshwater scarcity crisis. Mixed-integer Model Predictive Control (MPC) has emerged as an effective approach for addressing the complex scheduling problems in agricultural irrigation. However, the computational complexity of mixed-integer MPC still poses a significant challenge, particularly in large-scale applications. This study proposes an approach to enhance the computational efficiency of mixed-integer MPC-based irrigation schedulers by employing ReLU surrogate models to describe the soil moisture dynamics of the agricultural field. By leveraging the mixed-integer linear representation of the ReLU operator, the proposed approach transforms the mixed-integer MPC-based scheduler with a quadratic cost function into a mixed-integer quadratic program, which is the simplest class of mixed-integer nonlinear programming problems that can be efficiently solved using global optimization solvers. The effectiveness of this approach is demonstrated through comparative studies conducted on a large-scale agricultural field across two growing seasons, involving other machine learning surrogate models, specifically Long Short-Term Memory (LSTM) networks, and the widely used triggered irrigation scheduling method. The ReLU-based approach significantly reduces solution times -- by up to 99.5\% -- while achieving comparable performance to the LSTM approach in terms of water savings and Irrigation Water Use Efficiency (IWUE). Moreover, the ReLU-based approach maintains enhanced performance in terms of total prescribed irrigation and IWUE compared to the widely-used triggered irrigation scheduling method.

Johan Cederbladh, Antonio Cicchetti

In this paper we discuss the growing need for system behaviour to be validated and verified (V&V'ed) early in model-based systems engineering. Several aspects push companies towards integration of techniques, methods, and processes that promote specific and general V&V activities earlier to support more effective decision-making. As a result, there are incentives to introduce new technologies to remain competitive with the recently drastic changes in system complexity and heterogeneity. Performing V&V early on in development is a means of reducing risk for later error detection while moving key activities earlier in a process. We present a summary of the literature on early V&V and position existing challenges regarding potential solutions and future investigations. In particular, we reason that the software engineering community can act as a source for inspiration as many emerging technologies in the software domain are showing promise in the wider systems domain, and there already exist well formed methods for early V&V of software behaviour in the software modelling community. We conclude the paper with a road-map for future research and development for both researchers and practitioners to further develop the concepts discussed in the paper.

Oleksandr Kosenkov, Michael Unterkalmsteiner, Jannik Fischbach et al.

Context: Regulatory acts are a challenging source when eliciting, interpreting, and analyzing requirements. Requirements engineers often need to involve legal experts who, however, may often not be available. This raises the need for approaches to regulatory Requirements Engineering (RE) covering and integrating both legal and engineering perspectives. Problem: Regulatory RE approaches need to capture and reflect both the elementary concepts and relationships from a legal perspective and their seamless transition to concepts used to specify software requirements. No existing approach considers explicating and managing legal domain knowledge and engineering-legal coordination. Method: We conducted focus group sessions with legal researchers to identify the core challenges to establishing a regulatory RE approach. Based on our findings, we developed a candidate solution and conducted a first conceptual validation to assess its feasibility. Results: We introduce the first version of our Artifact Model for Regulatory Requirements Engineering (AM4RRE) and its conceptual foundation. It provides a blueprint for applying legal (modelling) concepts and well-established RE concepts. Our initial results suggest that artifact-centric RE can be applied to managing legal domain knowledge and engineering-legal coordination. Conclusions: The focus groups that served as a basis for building our model and the results from the expert validation both strengthen our confidence that we already provide a valuable basis for systematically integrating legal concepts into RE. This overcomes contemporary challenges to regulatory RE and serves as a basis for exposure to critical discussions in the community before continuing with the development of tool-supported extensions and large-scale empirical evaluations in practice.

Kelechi G. Kalu, Taylor R. Schorlemmer, Sophie Chen et al.

The primary theory of software engineering is that an organization's Policies and Processes influence the quality of its Products. We call this the PPP Theory. Although empirical software engineering research has grown common, it is unclear whether researchers are trying to evaluate the PPP Theory. To assess this, we analyzed half (33) of the empirical works published over the last two years in three prominent software engineering conferences. In this sample, 70% focus on policies/processes or products, not both. Only 33% provided measurements relating policy/process and products. We make four recommendations: (1) Use PPP Theory in study design; (2) Study feedback relationships; (3) Diversify the studied feedforward relationships; and (4) Disentangle policy and process. Let us remember that research results are in the context of, and with respect to, the relationship between software products, processes, and policies.

Sh. Nourinezhad, M.M. Rajabi, T. Fathi

Introduction Simulation of quantity and quality of surface runoff in mountainous watersheds is one of the most challenging topics in modeling due to its unique features, such as unusual topography and complex hydrological processes. One of the lesser-known aspects of modeling such catchments is the uncertainty analysis of water quality predictions, especially about the vital phosphorus parameter. Phosphorus is one of the important quality variables in water, and its increase in water resources can cause eutrophication phenomena in streams and reservoirs of dams. Due to the importance of the phosphorus parameter and the fact that water quality modeling has not been employed in the Karaj catchment area so far, in this research, total phosphorus has been modeled as a water quality parameter along with the flow and sediment discharge. This study aims to identify the most sensitive parameters of the model to flow, sediment, and total phosphorus discharge and calibrate, validate and analyze the parametric uncertainty of the SWAT model in predicting these three variables in a mountainous catchment. The case study was the catchment area of ​​the Karaj River upstream of Bileqan pond, which is one of the mountainous watersheds in Iran. There are two critical water structures along the Karaj River, namely Amirkabir dam and Bilqan pond. Amirkabir dam (Karaj) is a multi-purpose project that is constructed to supply drinking water to Tehran and regulate water for irrigation and agriculture in the suburbs of Karaj. The Bileqan pond is also the essential point of supply and transfer of drinking water in Tehran. Given the importance of this region in supplying water for different uses, providing a calibrated model for quantitative and qualitative variables of water can be the basis for decisions to apply future management scenarios in this basin.Materials and Methods The case study was the Karaj River catchment area upstream of Bilqan Basin, which with an average height of 2880 meters, is one of the mountainous areas located in the Alborz Mountains. This basin with an area of 1076 square kilometers in the north, includes parts of Mazandaran province. In the east and south of the catchment area includes parts of Tehran province and most of it is located in Alborz province. The average annual temperature and rainfall in this basin are 12.1 °C and 480 mm, respectively, and the average of 117 glacial days during the year is observed in this area. The long-term daily data of synoptic stations adjacent to the study area from the beginning of 1998 to the end of 2018 (21 years in total) was introduced to the model. Also, daily data of relative humidity, rainfall, minimum and maximum temperature, solar radiation hours, and wind speed as meteorological parameters measured at stations in the study area were introduced to the model. It should be noted that there was a lot of missing data in meteorological information, especially for daily temperature data. In addition to the above information, daily flow data discharged from Amirkabir dam and technical specifications of the dam were introduced to the model. In addition, orchard management information, including irrigation periods and information related to phosphate fertilizers used in regional orchards, were presented to the model. The global sensitivity analysis method was used to determine the sensitive parameters of the model. Furthermore, the SUFI2 algorithm was used in SWAT_CUP software to calibrate and analyze the parametric uncertainty of the SWAT model. This algorithm quantifies the output uncertainty by 95% prediction uncertainty boundaries.Results and Discussion According to the results of sensitivity analysis, the parameters Baseflow alpha-factor (ALPHA_BF), Manning’s “n” value for overland flow (OV_N), and Precipitation Laps rate (PLAPS) were the most sensitive parameters to flow, sediment, and total phosphorus, respectively. The best Nash-Sutcliffe (NS) coefficients for runoff, sediment, and total phosphorus simulation obtained in all stations and after full calibration and validation periods were equal to 0.76, 0.56, and 0.92, respectively. Simulation of the peak points of the diagram of all three quantities was also associated with increased uncertainty and decreased model prediction accuracy, but due to the placement of more than 70% of the measured runoff and sediment values and nearly 60% of the measured total phosphorus values in the prediction uncertainty boundaries generated by SUFI2 algorithm the final value of the parameters used in the calibration process can be appropriate for simulating future scenarios in similar mountain catchments. The main weakness of the model is simulating the peak points of flow and sediment discharge. In the case of flow and sediment discharge, the liability of modeling can be generalized due to the lack of accurate prediction of the snowmelt inflow to the river in spring, which begins to increase in February and reaches the peak point in May. A considerable number of missing data in meteorological stations can effectively reflect the lack of accurate model prediction at the peak points. In this region, missing daily temperature data compared to other meteorological parameters has been significant. The dependency of the SWAT model on many experimental and quasi-experimental models such as SCS-CN and MUSLE can be another factor affecting the weakness in predicting the peak points of the sediment discharge, as well.Conclusion According to the uncertainty analysis results, most of observed flow, sediment and total phosphorus discharge values were within the uncertainty prediction boundaries generated by the SUFI2 algorithm. The NS coefficient for all three variables has met the satisfactory modeling threshold. Therefore, it seems that the sensitive parameters identified and used in the calibration process in this study and their final values can be appropriate for modeling future scenarios for this study area and similar mountain catchments. One of the limitations of the present study was a large number of missing data in meteorological stations, especially for the temperature variable. Thus, providing required measured meteorological data to the model may emhance the simulation, especially at peak points.

زهرا اسلامی, خدایار عبدالهی

در مناطق خشک و نیمه‌خشک سهم قابل‌توجهی از بارندگی هرگز به نهرها یا آب‌های زیرزمینی نمی‌رسد که این بخش به نام تلفات بارندگی شناخته می‌شود و می‌تواند در میزان جریان رودخانه‌ای یا تغذیه آب‌های زیرزمینی نقش تعیین‌کننده‌ای داشته باشد. تلفات بارندگی در بسیاری از مدل‌های هیدرولوژیکی به‌عنوان یکی از اجزای اساسی پیش‌بینی مورد استفاده قرار می‌گیرد. در این مطالعه مؤلفه‌های تلفات هیدرولوژیکی برگاب، ذخیره چالابی، تبخیرتعرق، نفوذ و رطوبت خاک مرور شده و همچنین مشخصات مؤلفه‌های مذکور، مفاهیم کلی، مطالعات انجام‌شده و همچنین مقایسه روش‌های مفید محاسباتی این اجزاء تلفات هیدرولوژیکی، بیان‌شده‌اند. بررسی مطالعات نشان می‌دهد که با توجه به ماهیت پیچیده و تصادفی فرآیند بارندگی و عوامل متعدد مؤثر بر آن، هنوز از تلفات بارندگی درک جامعی نشده و در بسیاری از شبیه‌سازی‌ها به ساده‌سازی سامانه‌ها از طریق لحاظ نمودن نفوذ به‌عنوان تابع تلفات، بسنده شده است. در نتیجه، غالباً در کاربردهای عملی از مقادیر ثابتی برای تلفات در مدل‌سازی بارندگی استفاده می‌کنند که به لحاظ در نظر نگرفتن تغییرات زمانی و مکانی تلفات، منجر به برآورد نادرستی از کمیت رواناب می‌شود. بنابراین اولاً توجه به قالب زمان و مکان در مدل‌های تلفات بارندگی موجود و حتی مفاهیم آن توصیه می‌شود، ثانیاً باید توجه بیشتری به روابط بین اجزاء شود، زیرا مثلاً در مقیاس زمانی روزانه ممکن است یک مؤلفه نظیر تبخیر تعرق اهمیت کمتری نسبت به بازه‌های زمانی درازمدت پیدا کند یا در یک حوضه آبخیز شهری به علت دست‌کاری انسانی، فرآیندهای تلفات مشابه حوضه‌های طبیعی نباشد.

Gali Sheffi, Pedro Ramalhete, Erez Petrank

Multi-Version Concurrency Control (MVCC) is a common mechanism for achieving linearizable range queries in database systems and concurrent data-structures. The core idea is to keep previous versions of nodes to serve range queries, while still providing atomic reads and updates. Existing concurrent data-structure implementations, that support linearizable range queries, are either slow, use locks, or rely on blocking reclamation schemes. We present EEMARQ, the first scheme that uses MVCC with lock-free memory reclamation to obtain a fully lock-free data-structure supporting linearizable inserts, deletes, contains, and range queries. Evaluation shows that EEMARQ outperforms existing solutions across most workloads, with lower space overhead and while providing full lock freedom.

JIN Juliang, XU Jirong, CHEN Menglu et al.

【Background】 In previous work, we studied the results of the first-order partial connection coefficient and the subtraction set pair potential of the connection number, where we considered the directionality of the difference coefficient i in the partial positive connection number and the partial negative connection number. 【Objective】 The aim of this paper is to clarify the definition of the total partial coupling coefficient of the five element effect, determine its expression formula, describe its physical connotation, and evaluate its practical application in solving real water problems. 【Method】 This paper uses the method of analogy analysis to determine the calculation formula of the total partial coefficient of the five element effect by analyzing the existing results of the total partial coefficient of the three element effect, and further explains the physical connotation of the total partial coefficient of the five element effect with the help of the area of the trend curve of the partial coefficient, and applies it to the actual analysis of water problems. 【Result】 ①the results of the dynamic evaluation of water resources carrying capacity in Sichuan Province are highly consistent with the results of the full deflection coefficient of five element effect, and the full deflection coefficient of five element effect has the advantages of clearer development trend of the evaluation object, simpler calculation process, more reasonable evaluation results and more consistent with the physical connotation of the deflection coefficient; ②The diagnostic results of the five element effect partial coefficient on the vulnerability index of agricultural drought are consistent with the actual situation. The four indicators have great intraannual changes, and the impact on the comprehensive assessment results of drought vulnerability is more obvious. 【Conclusion】 The proposal of the five element effect total partial coupling coefficient expands the research scope of the effect total partial coupling coefficient, and the application in different cases has drawn more reasonable and credible calculation results, which has a great application prospect in solving similar problems in natural risk research.

Rodrigo Henrique Barbosa Monteiro, Maurício Ronny de Almeida Souza, Sandro Ronaldo Bezerra Oliveira et al.

Gamification has been used to motivate and engage participants in software engineering education and practice activities. There is a significant demand for empirical studies for the understanding of the impacts and efficacy of gamification. However, the lack of standard procedures and models for the evaluation of gamification is a challenge for the design, comparison, and report of results related to the assessment of gamification approaches and its effects. The goal of this study is to identify models and strategies for the evaluation of gamification reported in the literature. To achieve this goal, we conducted a systematic mapping study to investigate strategies for the evaluation of gamification in the context of software engineering. We selected 100 primary studies on gamification in software engineering (from 2011 to 2020). We categorized the studies regarding the presence of evaluation procedures or models for the evaluation of gamification, the purpose of the evaluation, the criteria used, the type of data, instruments, and procedures for data analysis. Our results show that 64 studies report procedures for the evaluation of gamification. However, only three studies actually propose evaluation models for gamification. We observed that the evaluation of gamification focuses on two aspects: the evaluation of the gamification strategy itself, related to the user experience and perceptions; and the evaluation of the outcomes and effects of gamification on its users and context. The most recurring criteria for the evaluation are 'engagement', 'motivation', 'satisfaction', and 'performance'. Finally, the evaluation of gamification requires a mix of subjective and objective inputs, and qualitative and quantitative data analysis approaches. Depending of the focus of the evaluation (the strategy or the outcomes), there is a predominance of a type of data and analysis.

Alex Serban, Koen van der Blom, Holger Hoos et al.

Following the recent surge in adoption of machine learning (ML), the negative impact that improper use of ML can have on users and society is now also widely recognised. To address this issue, policy makers and other stakeholders, such as the European Commission or NIST, have proposed high-level guidelines aiming to promote trustworthy ML (i.e., lawful, ethical and robust). However, these guidelines do not specify actions to be taken by those involved in building ML systems. In this paper, we argue that guidelines related to the development of trustworthy ML can be translated to operational practices, and should become part of the ML development life cycle. Towards this goal, we ran a multi-vocal literature review, and mined operational practices from white and grey literature. Moreover, we launched a global survey to measure practice adoption and the effects of these practices. In total, we identified 14 new practices, and used them to complement an existing catalogue of ML engineering practices. Initial analysis of the survey results reveals that so far, practice adoption for trustworthy ML is relatively low. In particular, practices related to assuring security of ML components have very low adoption. Other practices enjoy slightly larger adoption, such as providing explanations to users. Our extended practice catalogue can be used by ML development teams to bridge the gap between high-level guidelines and actual development of trustworthy ML systems; it is open for review and contribution

Austen Rainer

BACKGROUND: Software engineering is a human activity. People naturally make sense of their activities and experience through storytelling. But storytelling does not appear to have been properly studied by software engineering research. AIM: We explore the question: what contribution can storytelling make to human--centric software engineering research? METHOD: We define concepts, identify types of story and their purposes, outcomes and effects, briefly review prior literature, identify several contributions and propose next steps. RESULTS: Storytelling can, amongst other contributions, contribute to data collection, data analyses, ways of knowing, research outputs, interventions in practice, and advocacy, and can integrate with evidence and arguments. Like all methods, storytelling brings risks. These risks can be managed. CONCLUSION: Storytelling provides a potential counter--balance to abstraction, and an approach to retain and honour human meaning in software engineering.