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Ensuring food security in precision agriculture requires early prediction of soybean yield at various scales within the United States (U.S.), ranging from international to local levels. Accurate yield estimation is essential in preventing famine by providing insights into food availability during the growth season. Numerous deep learning (DL) algorithms have been developed to estimate soybean yield effectively using time-series remote sensing (RS) data to achieve this goal. However, the training data with short time spans can limit their ability to adapt to the dynamic and nuanced temporal changes in crop conditions. To address this challenge, we designed a 3D-ResNet-BiLSTM model to efficiently predict soybean yield at the county level across the U.S., even when using training data with shorter periods. We leveraged detailed Sentinel-2 imagery and Sentinel-1 SAR images to extract spectral bands, key vegetation indices (VIs), and VV and VH polarizations. Additionally, Daymet data was incorporated via Google Earth Engine (GEE) to enhance the model's input features. To process these inputs effectively, a dedicated 3D-ResNet architecture was designed to extract high-level features. These enriched features were then fed into a BiLSTM layer, enabling accurate prediction of soybean yield. To evaluate the efficacy of our model, its performance was compared with that of well-known models, including the Linear Regression (LR), Random Forest (RF), and 1D/2D/3D-ResNet models, as well as a 2D-CNN-LSTM model. The data from a short period (2019 to 2020) were used to train all models, while their accuracy was assessed using data from the year 2021. The experimental results showed that the proposed 3D-Resnet-BiLSTM model had a superior performance compared to the other models, achieving remarkable metrics (R2 = 0.791, RMSE = 5.56 Bu Ac−1, MAE = 4.35 Bu Ac−1, MAPE = 9%, and RRMSE = 10.49%). Furthermore, the 3D-ResNet-BiLSTM model showed a 7% higher R2 than the ResNet and RF models and an enhancement of 27% and 17% against the LR and 2D-CNN-LSTM models, respectively. The results highlighted our model's potential for accurate soybean yield predictions, supporting sustainable agriculture and food security. [ABSTRACT FROM AUTHOR]

The Last Planner System (LPS) aims to enhance planning reliability by reducing variability in construction processes. While LPS applications have been explored in construction and detailed design, its application in architectural design remains underrepresented due to its abstract nature. This study addresses this gap by proposing an LPS framework tailored for architectural design, utilizing LPS metrics to assess planning reliability. Key issues hindering formal planning methods' implementation are identified, and relevant LPS principles are aligned with these challenges, culminating in a conceptual LPS model designed for architectural projects. Building upon the conceptual model, an implementation model was developed and put into practice within an architectural design company in the United States, resulting in measured improvements in planning reliability and responsiveness. Additionally, it unveils hidden challenges associated with emerging tasks, guiding future design process enhancements. This study demonstrates how tracking design planning performance with LPS metrics can promote LPS adoption in architectural design, offering a benchmark for necessary interventions to achieve desired performance in architectural design. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Accurate prediction of solar energy is an important issue for photovoltaic power plants to enable early participation in energy auction industries and cost-effective resource planning. This article introduces a new deep learning-based multistep ahead approach to improve the forecasting performance of global horizontal irradiance (GHI). A deep convolutional long short-term memory is used to extract optimal features for accurate prediction of the GHI. The performance of such deep neural networks directly depends on their architectures. To deal with this problem, a swarm evolutionary optimization method, called the sine-cosine algorithm, is applied and advanced to automatically optimize the network architecture. A three-phase modification model is proposed to increase the diversity of population and avoid premature convergence in the optimization mechanism. The performance of the proposed method is investigated using three datasets collected from three solar stations in the east of the United States. The experimental results demonstrate the superiority of the proposed method in comparison to other forecasting models. [ABSTRACT FROM AUTHOR]

Copyright of Housing Environment / Środowisko Mieszkaniowe is the property of Chair of Housing Environment, Faculty of Architecture, Cracow University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Builder (1896-0642) is the property of PWB MEDIA Zdzieblowski sp.j. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The spaces represented in Edward Hopper's paintings are taken as a model by an academic project about light behavior in architecture, the goal of which is to develop a quantitative approach contrastable with the perception of natural light in such paintings. With the support of a physical model and a smartphone as measurement and verification instruments, the author tests the idea that it is possible to establish links between sensory registers and the performance of light in a certain precinct, using as a starting point the question posed by Hopper about the feasibility of light. [ABSTRACT FROM AUTHOR]

Actual evapotranspiration (ET a) plays a crucial role in the water and energy cycles of the earth. An accurate estimate of the ET a is essential for management of the water resources, agriculture, and irrigation, as well as research on atmospheric variations. Despite the importance of accurate ET a values, estimating and mapping them remains challenging due to the physical and biological complexity of the ET process. As a novel approach for rapid and reliable estimation of ET a , the present study develops automated deep learning (AutoDL) models that incorporate a metaheuristic optimization algorithm for image processing, architectural design, and hyperparameter tuning. The proposed AutoDL models integrate three different spatial and channel attention mechanisms, including a novel activated spatial attention mechanism (ASPAM), with the U-Net architecture. Bypassing the need for meteorological inputs, the proposed framework uses Moderate Resolution Imaging Spectrometer (MODIS) products and Digital Elevation Model (DEM) data as inputs. To evaluate the performance of the models, they are applied to three study areas in the United States with various climatic characteristics. According to the results, during the spring and summer, when the target values have higher certainty, the estimations are highly promising, with R2 as high as 0.91 and MAPE as low as 6.40%. Furthermore, the proposed ASPAM module improves the accuracy of ET a estimations compared to attention gate (AG) and squeeze and excitation (SE) attention modules. The results also indicate that the MODIS raw products and derived vegetation and water indices can predict ET a within a reliable range of accuracy, with the addition of DEM data marginally enhancing the models' performance. The automatic workflow of this model makes it significantly easy to use, contributing to its applicability and generalizability for enhancing atmospheric research. • A novel attention-based (ASPAM-) U-Net developed for actual evapotranspiration estimation. • Use of a single optical and thermal band dataset, eliminating the need for weather data inputs. • A comparative analysis of attention gate, squeeze and excitation, and ASPAM mechanisms. • Process automation, including optimal DL hyperparameters and architecture selection utilizing Harris Hawks Optimization. • Monthly evaluation of three U.S. regions with different hydroclimatological regimes over a 12-months period. • Evaluation of the impact of various inputs on model performance. [ABSTRACT FROM AUTHOR]

The article analyses and compares general education and specialised schools built in Lithuania, Europe and the USA during interwar years. The main problem analysed in the article is the correspondence between the architectural stylistics and functional spatial structure of interwar Lithuanian school buildings with the same typology buildings in the regional context. The aim of the article is to assess the essence of changes of architectural stylistics and functional spatial structure, what caused these changes. Interwar architecture in Lithuania has many of the main trends of the global architecture of that time, so undoubtedly interwar period is considered to be one of the most significant periods in the history of Lithuanian architecture, which has laid the foundations for the further development of Lithuanian architecture. [ABSTRACT FROM AUTHOR]

The research question addressed in this paper is as follows: how can planners create municipal-scale urban design plans? The authors analyze the San Francisco Urban Design Plan, the first comprehensive urban design plan for a major American city, as a case study to answer this question. Adopted in 1971, the plan focused on design objectives for the city and the social roles of urban design in people’s lives. It was a policy document, and included implementation techniques, but no guidance on architectural design. It was a departure from urban design planning practice at the time, which focused more on guidance for architecture and large-scale master plan models. [ABSTRACT FROM AUTHOR]

This Note discusses a significant, yet seldom noticed, circuit split concerning which substantial-similarity test properly protects architectural works--a look-and-feel test, a compilation test, or the Altai test? This split has the potential to create radically different levels of protection for similar sets of architectural works. This Note argues that the primary difference among the different circuits and their treatment of the issue is how aggressively each court "filters" out copyright-unprotected elements. In making this argument, this Note discusses the legislative history of copyright law and "architectural works," and examines the split among three different circuit courts. Ultimately, this Note suggests that courts apply the Second Circuit's Altai test, administering a careful analysis to "filter" out unoriginal, standard elements of an architectural work that do not deserve copyright protection. [ABSTRACT FROM AUTHOR]

Structural design codes of different countries provide engineers with data and procedures for design of the various structural components. Building design codes from USA, Europe, and Egypt are considered. Comparisons of the provisions for actions (loads), and for the resistance (strength) of sections in flexural and compressive axial loading are carried out. Several parameters are considered including variable actions for occupancy and different material strengths. The comparison is made considering both concrete and steel structures. Issues and consequences of mixing actions from one code and resistance from another code are also discussed. [ABSTRACT FROM AUTHOR]

The article examines the development of medical school building types in the U.S. in the 19th century and specifically its impact on modern medicine and the medical education reform that occured during the period. These medical school building types are the institute design, the single-building facility for preclinical studies, and the unified medical school-hospital. Also discussed are the impact of the schools' design ideas on the relationship between science and architecture, the reforms at the medical schools of Harvard University, University of Michigan, and the University of Pennsylvania.

This paper presents results from a qualitative analysis study conducted on the integration of structure in a building. If integration is to become more of a priority, what does this mean to structural engineers, and how do they add value? Eighty-five total participants--38 architects, 46 structural engineers, and one practicing as both--were interviewed in four major U.S. cities to record their experiences. The practitioners identified structural integration as being multifaceted, and the scope of structural integration is bigger and broader than what has been presented previously. Due to the need to understand the perspectives for each of the fields individually and the large number of responses, the analysis presented here encapsulates the responses from only the structural engineering professionals. Engineering practitioners incorporate aspects of time, professional relationships, and a collaborative environment with structural integration. Integration also includes working toward goals such as technical innovation, constructability, architectural design, combining structures with other systems, and ensuring that the owner's needs are met. Both the process and the aims lead to the physical articulation of the structure through its expression, detailing, and construction. A proposed framework for structural integration has been constructed from the responses to expand the current definition. With the changing practice environment, structural engineers need to consider what integrated design means to their profession, and this paper is intended to aid this process. [ABSTRACT FROM AUTHOR]

The article discusses the history of the Electrified Farm at the New York World's Fair in 1939. Topics discussed the potential to revolutionize America's farm life through electrification, the electric utility industry's sponsor of the Electrified Farm which is a one-acre working model of the use of electricity in the farm, and the design of the Electrified Farm by architectural company Wallace K. Harrison & J. André Fouilhoux. Also mentioned are the components of the Electrified Farm which include a greenhouse, barn, milkhouse and workshop.

The article offers the author's insights on the human architecture and its impact on the habitat of migratory birds. The author argues on the legal and ethical issues concerning the avian mortality in the U.S., the use of reflective and transparent glass in the architectural design, and the susceptibility of migratory birds on human architecture.