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

Cláudio Lúcio do Val Lopes, João Marcus Pitta, Fabiano Belém et al.

The integration of Artificial Intelligence (AI) into clinical settings presents a software engineering challenge, demanding a shift from isolated models to robust, governable, and reliable systems. However, brittle, prototype-derived architectures often plague industrial applications and a lack of systemic oversight, creating a ``responsibility vacuum'' where safety and accountability are compromised. This paper presents an industry case study of the ``Maria'' platform, a production-grade AI system in primary healthcare that addresses this gap. Our central hypothesis is that trustworthy clinical AI is achieved through the holistic integration of four foundational engineering pillars. We present a synergistic architecture that combines Clean Architecture for maintainability with an Event-driven architecture for resilience and auditability. We introduce the Agent as the primary unit of modularity, each possessing its own autonomous MLOps lifecycle. Finally, we show how a Human-in-the-Loop governance model is technically integrated not merely as a safety check, but as a critical, event-driven data source for continuous improvement. We present the platform as a reference architecture, offering practical lessons for engineers building maintainable, scalable, and accountable AI-enabled systems in high-stakes domains.

Hanwen Zhang, Laura A. Stevens, Ian J. Hewitt et al.

Subglacial blisters form due to the rapid drainage of supraglacial lakes into grounded ice sheets, and are characterised by elastic ice uplift and transient ice-velocity anomalies. Although blister occurrence is confirmed by observations, the dynamics of blisters and their impacts on ice flow remain poorly represented in current subglacial hydrology models, as typical cavity-channel system models cannot capture short-timescale blister formation, propagation, and relaxation. Here we present a unified, self-consistent modelling framework that directly couples blister evolution with the subglacial drainage system, extending existing subglacial hydrology models to account for transient responses to rapid lake drainage events. Numerical simulations, validated by field observations, reveal distinct seasonal behavior: during summer, lake drainage generates short-lived blisters that rapidly leak water into a pre-existing drainage system of efficient, channelised water pathways, whereas winter drainage results in persistent blisters that propagate and serve as the primary meltwater pathway at the ice-bed interface. The dynamics of blister propagation and leakage in our model are governed by effective viscosity and a characteristic leakage length scale, which reflects the connection between the blister and the surrounding hydrological network. This unified model offers a valuable tool for investigating blister dynamics and their interplay with subglacial hydrology, facilitating the interpretation of observed surface uplift and ice-velocity variations following supraglacial lake drainage events.

Marina Araújo, Júlia Araújo, Romeu Oliveira et al.

[Context] Domain knowledge is recognized as a key component for the success of Requirements Engineering (RE), as it provides the conceptual support needed to understand the system context, ensure alignment with stakeholder needs, and reduce ambiguity in requirements specification. Despite its relevance, the scientific literature still lacks a systematic consolidation of how domain knowledge can be effectively used and operationalized in RE. [Goal] This paper addresses this gap by offering a comprehensive overview of existing contributions, including methods, techniques, and tools to incorporate domain knowledge into RE practices. [Method] We conducted a systematic mapping study using a hybrid search strategy that combines database searches with iterative backward and forward snowballing. [Results] In total, we found 75 papers that met our inclusion criteria. The analysis highlights the main types of requirements addressed, the most frequently considered quality attributes, and recurring challenges in the formalization, acquisition, and long-term maintenance of domain knowledge. The results provide support for researchers and practitioners in identifying established approaches and unresolved issues. The study also outlines promising directions for future research, emphasizing the development of scalable, automated, and sustainable solutions to integrate domain knowledge into RE processes. [Conclusion] The study contributes by providing a comprehensive overview that helps to build a conceptual and methodological foundation for knowledge-driven requirements engineering.

Sonja M. Hyrynsalmi, Grischa Liebel, Ronnie de Souza Santos et al.

The discipline of software engineering (SE) combines social and technological dimensions. It is an interdisciplinary research field. However, interdisciplinary research submitted to software engineering venues may not receive the same level of recognition as more traditional or technical topics such as software testing. For this paper, we conducted an online survey of 73 SE researchers and used a mixed-method data analysis approach to investigate their challenges and recommendations when publishing interdisciplinary research in SE. We found that the challenges of publishing interdisciplinary research in SE can be divided into topic-related and reviewing-related challenges. Furthermore, while our initial focus was on publishing interdisciplinary research, the impact of current reviewing practices on marginalized groups emerged from our data, as we found that marginalized groups are more likely to receive negative feedback. In addition, we found that experienced researchers are less likely to change their research direction due to feedback they receive. To address the identified challenges, our participants emphasize the importance of highlighting the impact and value of interdisciplinary work for SE, collaborating with experienced researchers, and establishing clearer submission guidelines and new interdisciplinary SE publication venues. Our findings contribute to the understanding of the current state of the SE research community and how we could better support interdisciplinary research in our field.

Piotr Kacorzyk, Mirosław Kasperczyk, Barbara Wiśniowska-Kielian et al.

The aim of the study was to improve the habitat conditions in the initial development of a grass-legume mixture sown in the reconstructed river embankments along the Uszwica River in Kwików and the Vistula River in Kraków, Poland. For this purpose, after sowing the seeds, NPK fertilisation was used, along with the application of a hydrogel to limit the evaporation of water from the soil. Additionally, a non-woven fabric was used to cover the soil. The study was conducted in two stages. In the first stage, polymeric and five biodegradable non-woven fabrics were evaluated in laboratory conditions for their water absorption and retention capabilities. After this assessment, two biodegradable and one polymeric non-woven fabrics were selected for the second stage of field research. A grass- legume mixture consisting of five species of seeds: Lolium perenne L., Poa pratensis L., Festuca rubra L., Festuca arundinacea Schreb. and Trifolium repens L. was used for sowing the embankments. This study takes into account the concept of green economy aimed at addressing the challenges of securing difficult terrains, such as river embankments. The non-woven fabrics used to cover the soil had a positive effect on the initial development of plants, accelerating their emergence, and the degree of soil coverage. After two months post-sowing, the soil surface coverage under the non-woven fabrics was 50% higher compared to areas without such coverage. However, the type of non-woven fabrics and the hydrogel used did not have a significant impact on the initial development of seedlings.

LIU Qi, QU Zhongyi, BAI Yanying et al.

【Objective】 The leaf area index (LAI) is an important trait of plant canopies but challenging to measure accurately at large scales. We studied the feasibility of using multispectral imaging and machine learning to estimate the LAI of spring wheat. 【Method】 The experiment was conducted in a spring wheat field on the Tumochuan Plain in the Yellow River Basin, Inner Mongolia. Images of the spring wheat at the jointing, booting, and grain-filling stages were acquired using a multispectral camera mounted on a DJI P4M UAV. Selected vegetation indices were subjected to principal component analysis (PCA), and the resulting components were used to estimate LAI. We compared six models: multiple linear regression (MLR), decision tree regression (DTR), backpropagation neural network regression (BPNN), gradient boosting decision tree regression (GBDT), support vector machine regression (SVR), and random forest regression (RFR). LAI was calculated separately for each growth stage using different vegetation indices. 【Result】 LAI was significantly correlated with the normalized difference vegetation index (NDVI), modified simple ratio (MSR), ratio vegetation index (RVI), difference vegetation index (DVI), soil-adjusted vegetation index (SAVI), and normalized difference red edge index (NDRE). It showed a weak correlation with the renormalized difference vegetation index (RDVI) during the heading and grain-filling stages, with their correlation coefficients being 0.23 and 0.21, respectively. The BPNN model was most accurate during the jointing stage, with R2, RMSE, and MAE being 0.822, 0.305, and 0.257, respectively. In contrast, the RFR model performed best during the heading, grain-filling, and entire growth periods, with R2 being 0.613, 0.811 and 0.834, RMSE being 0.189, 0.150 and 0.174, and MAE being 0.126, 0.121 and 0.133, respectively. Additionally, the RFR model constructed using data from all three stages was more accurate than models derived from data at individual growth stages. 【Conclusion】 Multispectral data acquired via UAV, combined with machine learning algorithms, can accurately estimate the LAI of spring wheat at various growth stages. Models constructed using data from multiple growth stages are more accurate than those based on a single stage. The models are most accurate for the booting stage and least for the heading stage. Overall, the RFR model provided the most accurate LAI estimates across the three growth stages.

James S. Wheaton, Daniel R. Herber

Traditional requirements engineering tools do not readily access the SysML-defined system architecture model, often resulting in ad-hoc duplication of model elements that lacks the connectivity and expressive detail possible in a SysML-defined model. Without that model connectivity, requirement quality can suffer due to imprecision and inconsistent terminology, frustrating communication during system development. Further integration of requirements engineering activities with MBSE contributes to the Authoritative Source of Truth while facilitating deep access to system architecture model elements for V&V activities. The Model-Based Structured Requirement SysML Profile was extended to comply with the INCOSE Guide to Writing Requirements updated in 2023 while conforming to the ISO/IEC/IEEE 29148 standard requirement statement templates. Rules, Characteristics, and Attributes were defined in SysML according to the Guide to facilitate requirements definition and requirements V&V. The resulting SysML Profile was applied in two system architecture models at NASA Jet Propulsion Laboratory, allowing us to explore its applicability and value in real-world project environments. Initial results indicate that INCOSE-derived Model-Based Structured Requirements may rapidly improve requirement expression quality while complementing the NASA Systems Engineering Handbook checklist and guidance, but typical requirement management activities still have challenges related to automation and support with the system architecture modeling software.

Sayan Chatterjee, Ching Louis Liu, Gareth Rowland et al.

The increasing popularity of AI, particularly Large Language Models (LLMs), has significantly impacted various domains, including Software Engineering. This study explores the integration of AI tools in software engineering practices within a large organization. We focus on ANZ Bank, which employs over 5000 engineers covering all aspects of the software development life cycle. This paper details an experiment conducted using GitHub Copilot, a notable AI tool, within a controlled environment to evaluate its effectiveness in real-world engineering tasks. Additionally, this paper shares initial findings on the productivity improvements observed after GitHub Copilot was adopted on a large scale, with about 1000 engineers using it. ANZ Bank's six-week experiment with GitHub Copilot included two weeks of preparation and four weeks of active testing. The study evaluated participant sentiment and the tool's impact on productivity, code quality, and security. Initially, participants used GitHub Copilot for proposed use-cases, with their feedback gathered through regular surveys. In the second phase, they were divided into Control and Copilot groups, each tackling the same Python challenges, and their experiences were again surveyed. Results showed a notable boost in productivity and code quality with GitHub Copilot, though its impact on code security remained inconclusive. Participant responses were overall positive, confirming GitHub Copilot's effectiveness in large-scale software engineering environments. Early data from 1000 engineers also indicated a significant increase in productivity and job satisfaction.

HU Guirong, LI Shiying, JIN Yanjing et al.

【Objective】 The asymmetric Venturi fertilizer injector is a device to simultaneously supply water and nutrients to crops through a drip irrigation system. Its performance is influenced by various factors. In this paper, we experimentally study the impact of the offset distance of the central axis in the diffusion section on fertilizer adsorption. 【Method】 Five asymmetric Venturi injectors with different diffusion sections were studied. Their fertilizer absorption was experimentally and numerically studied. The fertilizer absorption rate, critical pressure difference and the critical pressure at the inlet for fertilizer absorption were compared and analyzed between the five injectors. 【Result】 Under normal working conditions, the fertilizer absorption rate linearly increased with the inlet pressure. When the pressure difference between the inlet and outlet was 0.15 MPa, the fertilizer absorption rate maximized. The critical pressure difference and critical inlet pressure both increased with the increase in the outlet pressure. Compared with original asymmetric Venturi injector (F1), the asymmetric Venturi injector with eccentric downward diffusion section (F5) increased fertilizer absorption rate and efficiency by 13.03%~40.16% and 12.09%~39.13%, respectively. The increase, however, gradually decreased with the increase in the inlet pressure. Compared with F1, F5 increased the maximum fertilizer absorption rate by up to 13.03% and reduced the critical pressure difference by 7.69%. 【Conclusion】 When working at normal conditions, reducing the outlet pressure was beneficial to reducing the critical pressure at the inlet for fertilizer absorption. Moving the diffusion section away from the side of the fertilizer suction pipe can reduce local water head loss, make pressure at the throat more negative, thereby increasing the flow rate of fertilizer into the injector and reducing the critical pressure difference for fertilizer absorption. Our findings can help improve the design of the Venturi fertilizer injector for drip irrigation-fertigation systems.

M. Rafati, M. Malekzadeh, M. Firoozi

Intruduction Increasing industrial activities with the production of pollutants, including heavy metals, is one of the serious problems of modern communities, which has led to their accumulation in the environment. Heavy metals are also one of the important pollutants in landfill leachate. Plants and soil near the landfill may be contaminated by the leachate. Landfilling is the oldest method of solid waste disposal which can be a threat to the environment and health. Due to its easy operation and cost-effective, landfill is the most widely used method of municipal solid waste disposal in the world. Pollution cleaning technologies to reduce the harmful effects in the locations contaminated with heavy metals can be done by physical, chemical and biological methods. Phytoremediation, as a biological method, uses the green plants to extract, sequester, and detoxify pollutants. This method is a low-cost technique, environmentally friendly, and due to the non-production of by-products, is non-destructive for natural ecosystems. Considering the high moisture of wastes in Iran and their potential to produce leachate, as well as the possibility of contamination of water and soil in the landfill, especially with heavy metals, this study was conducted with the aim of evaluating the accumulation of lead (Pb) and cadmium (Cd) heavy metals in the soil, shoots and roots of artiplex (Atriplex sp.) and oleander (Nerium olander) plants in Aradkooh landfill of Tehran.   Materials and Methods This study was conducted in Aradkooh landfill which is located in the south of Tehran in the Kahrizak region. About 5200 tons of municipal solid waste were sent to this landfill every day. A part of the solid waste in Aradkoh was placed in various processes to energy and compost, and about 2500 tons of the solid waste was landfilled. According to previous reports, it is estimated that 250 cubic meters of leachate are produced daily in the Aradkoh landfill. In the studied landfill, there is an atriplex plant in four areas and a hand-planted oleander in one area. Ten samples of soil, root, and shoot, totaling 120 total were randomly selected from each growing area of the atriplex plant. Oleander shoots and soil were also tested from 10 different plants for a total of 40 samples. Then the levels of Cd and Pb in the soil, roots, and shoots were assessed. In this study, the outcomes were analyzed employing four key indices: the bioconcentration factor (BCF), the translocation factor (TF), the pollution index (PI), and PINemerow. The BCF and TF indices were employed to assess the phytoextraction and phytostabilization capabilities of plants, while the PI and PINemerow methods were used to pinpoint the most environmentally hazardous heavy metal in the soil.Results and Discussion  According to the results, the concentration of Pb and Cd in  shoots of atriplex  area 2 (with an average of 19.7 and 5.75 mg/kg, respectively) were significantly higher than in other areas, while the concentration of these metals in root of oleander (with an average of 8.17 and 1.06 for Pb and Cd, respectively) were higher than the shoot. The amount of Pb element in soil of the oleander plant (with an average of 35.13 mg/kg) and Cd in soil of the atriplex area 2 (with an average of 3.78 mg/kg) were significantly higher than other areas. Additionally, the levels of heavy metals in the soil of two plants were higher than the Nemerow index, which indicated high levels of pollution in the sampling areas, but still below the safe levels that was set by national standards (3.9 and 300 mg/kg for Cd and Pb respectively) and the World Health Organization (5 and 40 mg/kg for Cd and Pb, respectively). In addition, bioaccumulation factor of shoot in all growth atriplex areas for Pb and Cd (with an average of 1.44 and 1.3, respectively) were higher than 1.0 while, the root bioaccumulation factors of this plant in any of the growth areas, were not higher than 1.0. In the case of oleander, the shoot and root bioconcentration factors  for Pb and Cd were not reported more than one.   Conclusion In general, it appears that atriplex, a native plant in the Aradkooh landfill, exhibits superior capabilities for absorbing heavy elements compared to oleander. Therefore, atriplex seems well-suited for the extraction of Pb and Cd from the soil, as it can accumulate these metals in its shoots. In contrast, oleander is not well-suited for phytostabilization or phytoextraction of these elements, as it exhibits limited ability to accumulate these heavy metals in its roots and shoots. Consequently, atriplex can be a valuable choice as a resilient species for phytoremediation projects in landfills and areas near mines. It is worth noting that the Pb content in the soil is higher than that of Cd. Although both metals fall within the permissible limits of national and WHO standards, the soil in the Aradkooh landfill is considered to be significantly polluted based on the Nemerow index.

S. Safarpour, M. Maddah

Water is important as a prerequisite for the development and survival of the human race and plays a fundamental role in providing and achieving the social, economic, and environmental goals and priorities of any country. With the continuation of the unfavorable trend of the situation of water resources in the world and the prediction of the continuation of the water crisis, the problem of water shortage is continuously increasing. In this framework, this article tries to identify the factors affecting it by examining the various dimensions of water poverty, including driving forces, pressure, states, and impact, using the structural equation modeling approach - partial least squares method (PLS-SEM) in 2019. The results of the estimation of the model show that, firstly, the driving forces have a positive and significant effect on the pressure structures and the impact of water poverty at the level of the provinces of the country. Secondly, the pressure structure has a negative and significant effect on the state of water poverty. Thirdly, the structure of the states, which expresses environmental changes, has a negative and significant effect on the impacts of water poverty. Also, among the factors affecting water poverty in 2019, the variables are the number of doctors per ten thousand people with a coefficient of 0.934, the ratio of irrigated land to total cultivated land with a coefficient of 0.893, total drinking water consumption with a coefficient of 0.888, and desert phenomena with a coefficient of 1 are the most important influencing factors.

DOU Xiangzhou, QIAN Xiuhong, PAN Weiyan et al.

【Objective】 The Xiaoqing River is located in Shandong province. In this paper, we analyze the contaminants in its estuary and assess its water quality. 【Method】 We selected the section from Shicun to Yangjiaogou for analysis. Water quality was evaluated based on data measured from 2019 to 2021 from four water sampling locations in the section. The main pollutants in the locations were analyzed using the principal component analysis method; we also analyzed the origin of these pollutants. 【Result】 Water quality in sampling locations in the section had improved from 2019 to 2021, with the water quality level changing to Class IV in 2021. The pollutants that exceeded the standard at these locations are total nitrogen (TN), of which nitrate (NO3-) is the main pollutant. NO3- at Shicun was affected by both non-point pollution and domestic sewage, while the origin of NO3- at Houxinzhuang was sewage and manure. Meteorological factors such as temperature and rainfall had indirect affect in water quality in the estuary. 【Conclusion】 The comprehensive water quality identification index combined with the combinatorial integration method is accurate for assessing water quality. The main pollutants in the estuary of Xiaoqing River are total nitrogen, especially nitrate.

Yuji Saikai, Allan Peake, Karine Chenu

Deep reinforcement learning has considerable potential to improve irrigation scheduling in many cropping systems by applying adaptive amounts of water based on various measurements over time. The goal is to discover an intelligent decision rule that processes information available to growers and prescribes sensible irrigation amounts for the time steps considered. Due to the technical novelty, however, the research on the technique remains sparse and impractical. To accelerate the progress, the paper proposes a principled framework and actionable procedure that allow researchers to formulate their own optimisation problems and implement solution algorithms based on deep reinforcement learning. The effectiveness of the framework was demonstrated using a case study of irrigated wheat grown in a productive region of Australia where profits were maximised. Specifically, the decision rule takes nine state variable inputs: crop phenological stage, leaf area index, extractable soil water for each of the five top layers, cumulative rainfall and cumulative irrigation. It returns a probabilistic prescription over five candidate irrigation amounts (0, 10, 20, 30 and 40 mm) every day. The production system was simulated at Goondiwindi using the APSIM-Wheat crop model. After training in the learning environment using 1981-2010 weather data, the learned decision rule was tested individually for each year of 2011-2020. The results were compared against the benchmark profits obtained by a conventional rule common in the region. The discovered decision rule prescribed daily irrigation amounts that uniformly improved on the conventional rule for all the testing years, and the largest improvement reached 17% in 2018. The framework is general and applicable to a wide range of cropping systems with realistic optimisation problems.

Sehrish Malik, Moeen Ali Naqvi, Leon Moonen

There is an increasing need to assess the correct behavior of self-adaptive and self-healing systems due to their adoption in critical and highly dynamic environments. However, there is a lack of systematic evaluation methods for self-adaptive and self-healing systems. We proposed CHESS, a novel approach to address this gap by evaluating self-adaptive and self-healing systems through fault injection based on chaos engineering (CE) [ arXiv:2208.13227 ]. The artifact presented in this paper provides an extensive overview of the use of CHESS through two microservice-based case studies: a smart office case study and an existing demo application called Yelb. It comes with a managing system service, a self-monitoring service, as well as five fault injection scenarios covering infrastructure faults and functional faults. Each of these components can be easily extended or replaced to adopt the CHESS approach to a new case study, help explore its promises and limitations, and identify directions for future research. Keywords: self-healing, resilience, chaos engineering, evaluation, artifact

حمیدرضا کمالی, محمد عبداللهی پور, محمد جواد نحوی نیا

استفاده از مدل‌سازی یکی از گزینه‌‌های مناسب برای جایگزینی آزمایشات مزرعه‌ای به منظور صرفه‌جویی در زمان و هزینه است. مدل SALTMED یکی از مدل‌های عمومی برای شبیه‌سازی واکنش گیاهان مختلف تحت تنش شوری و خشکی است. این پژوهش با هدف ارزیابی این مدل برای گیاه گندم در اقلیم خشک در شهرستان بیرجند در خراسان جنوبی انجام شد. تیمارهای در‌نظر‌گرفته‌شده در این تحقیق شامل تنش خشکی 50، 75، 100 و120 درصد نیاز آبی و تنش شوری ناشی از آب آبیاری با شوری‌های 4/1، 5/4 و 6/9 دسی‌زیمنس بر متر بود و آزمایشات در سه تکرار انجام شد. نتایج شاخص‌های آماری، نشان‌دهنده ریشه میانگین مربعات خطای نرمال (NRMSE) کمتر از 10 درصد و ضریب تعیین 99/0 و 96/0 بین مقادیر اندازه‌گیری‌شده و تخمینی محصول در مراحل واسنجی و ارزیابی بود. همچنین مدل توانست روند تغییرات زمانی تبخیر و تعرق و نیز تغییرات زمانی و عمقی شوری خاک را به صورت مطلوبی در طول فصل کشت برآورد کند. بنابراین با توجه به نتایج پژوهش، مدل SALTMED، از کارایی و دقت مناسبی برای پیش بینی محصول و همچنین واکنش‌های گیاهی گندم در شرایط مختلف کم آبیاری و درجات مختلف شوری در مناطق خشک برخوردار است.

CHEN Chaofan, MAO Weibing, SUN Yuxia et al.

【Objective】 The delta of Yellow River is characterized by soil salinity. Different methods have been proposed to remediate it, and the objective of this paper is to investigate the efficacy of amending it with Yellow River sediments in reliving the salinity and improving winter wheat yield. 【Method】 The field experiment was conducted in a saline clay soil which was amended with Yellow River sediment at rates of 0 kg/m2, 5 kg/m2, 10 kg/m2, 15 kg/m2, 20 kg/m2, 25 kg/m2, 30 kg/m2, 35 kg/m2 respectively. For each treatment, we measured the changes in saturated hydraulic conductivity, soil water content and soil salinity, as well as grain yield and yield traits. 【Result】 Soil amendment reduced the soil bulk density, with the decrease increased with the amending rate. The sediment amendment also increased the saturated hydraulic conductivity, exponentially as sediment application increased. The amendment reduced soil moisture content and salt content in the 0~40 cm of soil layer. Applying 15 kg/m2 of the sediment reduced the soil water content and salt content in the 0~20 cm and 20-40cm of soils by 16.61% and 22.89%, and 12.86% and 22.44%, respectively, compared to the control without amendment. Soil amendment also increased winter wheat yield. As the sediment application increased, the yield increased first followed by decline. Of all treatments we compared, applying 15 kg/m2 of the sediment was optimal, increasing the yield to 7 530.98 kg/hm2, a 32.78% increase over the control. 【Conclusion】 Amending the saline clay soil in the delta of the Yellow River with Yellow River sediment at a rational rate can improve soil quality and winter wheat yield. For our experiments, the optimal application rate was 15 kg/m2.

علیرضا کیانی, محمد رضا یزدانی, محمد تقی فیض بخش

چهار روش آبیاری (غرقاب دائم، تناوبی، بارانی، تیپ) و سه روش کشت (مستقیم بذر و مستقیم نشاء بر بستر غیرپادل یا بدون گلخرابی و نشائی سنتی) از نظر عملکرد، مصرف آب و بهره­وری آب برنج در قالب طرح کرت­های نواری بر اساس طرح پایه بلوک­های کامل تصادفی با سه تکرار به مدت دو سال زراعی (1398 و 1399) در گرگان بررسی شدند. مقایسه عملکردهای برنج نشان داد که بالاترین عملکرد ( 8206 کیلوگرم در هکتار) مربوط به کشت نشائی سنتی با روش آبیاری غرقابی بود و در بقیه روش­های آبیاری اختلاف معنی­داری بین عملکردها مشاهده نشد. در کشت نشائی، با تغییر آبیاری سنتی به آبیاری بارانی، متناوب و آبیاری قطره­ای به ترتیب عملکرد در حدود 14، 9 و 11 درصد کاهش داشت. بالاترین مصرف آب مربوط به روش آبیاری غرقابی در کشت مستقیم بذر (12490 متر مکعب در هکتار) و کشت نشائی (11967 متر مکعب در هکتار) بود. با تغییر شیوه آبیاری از غرقاب به قطره­ای در کشت سنتی نشاء در زمین پادل شده، اگرچه عملکرد در حدود 11 درصد کاهش یافت ولی در مقابل مصرف آب در حدود 39 درصد کاهش و در نتیجه بهره-وری آب در حدود 22 درصد افزایش داشت. با تبدیل کشت سنتی نشاء و روش آبیاری غرقابی به کشت مستقیم نشاء و روش آبیاری قطره­ای عملکرد در حدود 24 درصد و مقدار آب در حدود 45 درصد کاهش یافت و بهره­وری آب در این حالت به 9/0 کیلوگرم در متر مکعب رسید که در شرایط حاضر به عنوان بهترین گزینه برای حفظ توأم منابع آبی و تولید انتخاب می­شود.

Hironori Washizaki

It is essential to discuss the role, difficulties, and opportunities concerning people of different gender in the field of software engineering research, education, and industry. Although some literature reviews address software engineering and gender, it is still unclear how research and practices in Asia exist for handling gender aspects in software development and engineering. We conducted a systematic literature review to grasp the comprehensive view of gender research and practices in Asia. We analyzed the 32 identified papers concerning countries and publication years among 463 publications. Researchers and practitioners from various organizations actively work on gender research and practices in some countries, including China, India, and Turkey. We identified topics and classified them into seven categories varying from personal mental health and team building to organization. Future research directions include investigating the synergy between (regional) gender aspects and cultural concerns and considering possible contributions and dependency among different topics to have a solid foundation for accelerating further research and getting actionable practices.

Lars Reimann, Günter Kniesel-Wünsche

Development of machine learning (ML) applications is hard. Producing successful applications requires, among others, being deeply familiar with a variety of complex and quickly evolving application programming interfaces (APIs). It is therefore critical to understand what prevents developers from learning these APIs, using them properly at development time, and understanding what went wrong when it comes to debugging. We look at the (lack of) guidance that currently used development environments and ML APIs provide to developers of ML applications, contrast these with software engineering best practices, and identify gaps in the current state of the art. We show that current ML tools fall short of fulfilling some basic software engineering gold standards and point out ways in which software engineering concepts, tools and techniques need to be extended and adapted to match the special needs of ML application development. Our findings point out ample opportunities for research on ML-specific software engineering.

Ian A. Cosden

The Princeton Research Software Engineering Group has grown rapidly since its inception in late 2016. The group, housed in the central Research Computing Department, comprised of professional Research Software Engineers (RSEs), works directly with researchers to create high quality research software to enable new scientific advances. As the group has matured so has the need for formalizing operational details and procedures. The RSE group uses an RSE partnership model, where Research Software Engineers work long-term with a designated academic department, institute, center, consortium, or individual principal investigator (PI). This article describes the operation of the central Princeton RSE group including funding, partner & project selection, and best practices for defining expectations for a successful partnership with researchers.