ObjectiveThe low-altitude economy covers low-altitude manufacturing, flight operations, support services and comprehensive service industries, and has the characteristics of spatially three-dimensional, regional dependence, digital ecology, industrial integration and radiation driving. With the continuous development of digitization and informatization, these characteristics increasingly affect the interaction between low-altitude activities and urban and natural environments, which provides new ideas for the development of landscape architecture, and the coordinated development of the two is an important issue in the transformation of landscape architecture.MethodsThe knowledge map method was used to analyze the research status of environmental low-altitude economy at home and abroad. By combing and reading relevant literature at home and abroad, the research trends of low-altitude economy in logistics, aviation, ecological monitoring and other fields were systematically analyzed by reviewing literature research, case studies and comparative analysis. ResultsBy analyzing the domestic and foreign research, the internal mechanism of the cross research between landscape architecture and low-altitude economy is revealed four aspects. In the aspect of technology application, low-altitude aircraft tend to be transformed from perception tools to "design intelligence" which can guide ecological design and space construction. In the aspect of spatial planning, landscape architecture will realize the spatial transformation from plane extension to three-dimensional reconstruction under the development of low-altitude economy. In the aspect of ecological impact, the research focus has changed from identifying environmental risks by using low-altitude facilities to systematic assessment and control of ecology. In the aspect of humanistic experience, the combination of low-altitude economy and cultural narrative has further stimulated the vitality of landscape architecture discipline. It is found that under the influence of low-altitude economy, the development of landscape architecture faces some new problems, such as imperfect policies and regulations, insufficient adaptability of spatial planning system, systematic lack of ecological protection, technical bottleneck restriction, homogenization dilemma of cultural and tourism integration, including lack of unified standards for low-altitude facility design, traditional two-dimensional planning being difficult to meet the needs of air-space coordination, ecological destruction caused by noise and habitat disturbance, lack of ecological protection system, etc. There are technical bottlenecks in data processing and flight stability; homogenization of tourism products, focusing on tourism over cultural innovation. In order to promote the coordinated development of the two, this paper puts forward the implementation path of the integration of low-altitude economy and landscape architecture: to ensure the adaptation of policies and regulations, to improve policies and regulations and technical standards, to formulate low-altitude greening design and ecological evaluation standards, and to lay a foundation for the integration of landscape architecture and low-altitude economy; Conduct spatial value evaluation, clarify the use, development subject and income distribution mechanism of each low-altitude area, promote the market-oriented operation of public resources, and use unmanned aerial vehicles to carry out ecological background analysis and evaluate the ecological carrying capacity of low-altitude activities; Conduct functional compound planning, make landscape architecture break through the limitation of traditional ground perspective, bring low-altitude airspace into the vertical space system of landscape architecture, add low-altitude related infrastructure in the garden, and realize efficient coordinated utilization of airspace and ground resources; In ecological service monitoring, we should increase the investment in R&D of UAV technology, low-altitude aircraft noise reduction technology, flight safety guarantee technology, etc., improve the intelligent level of landscape architecture monitoring and management, and establish a new ecological assessment mode; Promote the integrated development of culture and tourism, break through the homogenization dilemma from three dimensions of cultural empowerment, spatial differentiation and experience depth, and integrate garden cultural elements into low-altitude experience links, to improve the overall operation effect. ConclusionBased on the research, we have drawn conclusions in three aspects. 1) The global low-altitude economy industry will become the next development hotspot, and it should accelerate the integration with transportation logistics, cultural tourism and other formats, expand more application scenarios, promote the integration of landscape architecture and related industries, and activate the new vitality of landscape architecture. 2) Green space and parks in cities will become important carriers for low-altitude transportation in the future, and planning and design of low-altitude composite public space will be the focus of research, and research will move from two-dimensional garden aesthetic space to three-dimensional traffic spatial pattern. 3) The development of unmanned aerial vehicle and related technologies provide refined intelligent solutions for intelligent garden management, and low-altitude monitoring data provide new tools for ecological value assessments of gardens, significantly improve ecological monitoring and management levels.
Aesthetics of cities. City planning and beautifying, Architectural drawing and design
With the rise of large language models (LLMs), LLM agents capable of autonomous reasoning, planning, and executing complex tasks have become a frontier in artificial intelligence. However, how to translate the research on general agents into productivity that drives industry transformations remains a significant challenge. To address this, this paper systematically reviews the technologies, applications, and evaluation methods of industry agents based on LLMs. Using an industry agent capability maturity framework, it outlines the evolution of agents in industry applications, from "process execution systems" to "adaptive social systems." First, we examine the three key technological pillars that support the advancement of agent capabilities: Memory, Planning, and Tool Use. We discuss how these technologies evolve from supporting simple tasks in their early forms to enabling complex autonomous systems and collective intelligence in more advanced forms. Then, we provide an overview of the application of industry agents in real-world domains such as digital engineering, scientific discovery, embodied intelligence, collaborative business execution, and complex system simulation. Additionally, this paper reviews the evaluation benchmarks and methods for both fundamental and specialized capabilities, identifying the challenges existing evaluation systems face regarding authenticity, safety, and industry specificity. Finally, we focus on the practical challenges faced by industry agents, exploring their capability boundaries, developmental potential, and governance issues in various scenarios, while providing insights into future directions. By combining technological evolution with industry practices, this review aims to clarify the current state and offer a clear roadmap and theoretical foundation for understanding and building the next generation of industry agents.
Abstract This paper provides a comprehensive study on the structural behaviour of steel-timber composite elements through reviewing their composite assembly effect, capacity improvements, fire resistance, durability, maintenance, design considerations and material selection recommendations. The study begins by examining the material properties of steel and timber, including their individual characteristics. The interactional mechanisms between steel and timber within composite structures are explored to explain how they enhance the overall strength and stiffness. The load-bearing capacity and performance of steel-timber composites are evaluated through considering factors such as geometry and connection methods. The fire performance of steel-timber composites is also analysed. Manufacturing techniques such as assembly and joining methods for composite elements, are discussed. Finally, key findings and future work recommendations are summarized to further enhance the understanding, design, and implementation of steel-timber composite elements in the construction industry.
Materials of engineering and construction. Mechanics of materials, Environmental engineering
Rahma Sandhi Prahara, Nur Dinah Fauziyah, Diah Syifaul A’yuni
This study explores how age, education, experience, and wages affect labor productivity in the housing sector of Mojosari, Mojokerto Regency. With rapid urbanization and rising housing demand, understanding these factors is crucial for improving workforce performance. Using a quantitative approach and multiple linear regression, data was gathered from 150 construction workers in Mojosari through random sampling. The analysis found that all four factors—age, education, experience, and wages—significantly impact productivity. Education had the greatest influence, emphasizing the importance of skill development. Both experience and wages also positively affected productivity, while age showed a mixed effect, with productivity increasing until a certain age before declining. The model explained 62% of the productivity variation. The findings suggest the need for policies focusing on workforce training, fair wages, and better management to enhance productivity. Investing in education and skills development will be key for sustaining growth in the housing sector. This research provides valuable insights for improving labor productivity in Indonesia's housing industry, particularly in rapidly urbanizing areas.
The Karychsay deposit in Uzbekistan is an important site for the extraction and beneficiation of various types of mineral resources, especially leucocratic granites. Leucocratic granites are important igneous rocks that contain significant amounts of feldspar and quartz and dark colored minerals in smaller quantities. Granites of this nature have found widespread use in important industries such as construction, industry, in the production of cladding materials and for the production of a number of other economically important metals. The paper considers the necessary properties of leucocratic granites such as durability, strength and attractiveness these rock formations which are essential items in the growing demand for high quality materials for construction and architectural design. The Karichsay deposit in Uzbekistan is one of the promising sources of leucocratic granites. One of the sections of this place “Vostochny”, which contains a significant amount of reserves of these minerals, is of interest for further exploitation for profit. Despite this, the heterogeneity of the composition of the mined raw materials pushes engineers to develop productive enrichment methods to improve their physical and chemical characteristics.
Nowadays, electric robots play big role in many fields as they can replace humans and/or decrease the amount of load on humans. There are several types of robots that are present in the daily life, some of them are fully controlled by humans while others are programmed to be self-controlled. In addition there are self-control robots with partial human control. Robots can be classified into three major kinds: industry robots, autonomous robots and mobile robots. Industry robots are used in industries and factories to perform mankind tasks in the easier and faster way which will help in developing products. Typically industrial robots perform difficult and dangerous tasks, as they lift heavy objects, handle chemicals, paint and assembly work and so on. They are working all the time hour after hour, day by day with the same precision and they do not get tired which means that they do not make errors due to fatigue. Indeed, they are ideally suited to complete repetitive tasks.
When validated neural networks (NNs) are pruned (and retrained) before deployment, it is desirable to prove that the new NN behaves equivalently to the (original) reference NN. To this end, our paper revisits the idea of differential verification which performs reasoning on differences between NNs: On the one hand, our paper proposes a novel abstract domain for differential verification admitting more efficient reasoning about equivalence. On the other hand, we investigate empirically and theoretically which equivalence properties are (not) efficiently solved using differential reasoning. Based on the gained insights, and following a recent line of work on confidence-based verification, we propose a novel equivalence property that is amenable to Differential Verification while providing guarantees for large parts of the input space instead of small-scale guarantees constructed w.r.t. predetermined input points. We implement our approach in a new tool called VeryDiff and perform an extensive evaluation on numerous old and new benchmark families, including new pruned NNs for particle jet classification in the context of CERN's LHC where we observe median speedups >300x over the State-of-the-Art verifier alpha,beta-CROWN.
Carlos Alberto Durigan Junior, Kumiko Oshio Kissimoto, Fernando Jose Barbin Laurindo
The fourth industrial revolution promotes the integration of Information Technology (IT) and strategic resources. New IT demands and uses have been leading to changes in business processes and corporate governance. Lately, the financial industry has adopted a new integrated banking model known as Open Banking (OB) and the advent of cryptocurrencies has led to the Digital Economy (DE) materialization. Considering these facts, this paper expects to point out through literature review some IT enabling factors that allow the conception of a new industry design (or governance) specifically in the financial industry illustrated by the cases of the Open Banking and Digital Economy. This paper is structured mostly on literature review, accompanied by results, discussions, and finally, conclusions are presented. It was found five potential enabling factors. Keywords: Digital Economy, Information Technology (IT), Open Banking.
Silvia García-Méndez, Francisco de Arriba-Pérez, María del Carmen Somoza-López
Artificial Intelligence (AI) can potentially transform the industry, enhancing the production process and minimizing manual, repetitive tasks. Accordingly, the synergy between high-performance computing and powerful mathematical models enables the application of sophisticated data analysis procedures like Machine Learning. However, challenges exist regarding effective, efficient, and flexible processing to generate valuable knowledge. Consequently, this work comprehensively describes industrial challenges where AI can be exploited, focusing on the dairy industry. The conclusions presented can help researchers apply novel approaches for cattle monitoring and farmers by proposing advanced technological solutions to their needs.
Psychosocial hazards adversely affect the mental health of construction practitioners. However, limited construction studies have examined the effect of the interplay of psychosocial hazards on mental health. This research comprehensively explored the qualitative and quantitative relationships between psychosocial hazards and mental health in the construction industry through meta-analysis, semi-structured interviews, and Bayesian network modelling. The research findings are expected to provide valuable insights for construction practitioners in effectively managing psychosocial hazards and creating mentally healthy workplaces.
Determining industry and product/service codes for a company is an important real-world task and is typically very expensive as it involves manual curation of data about the companies. Building an AI agent that can predict these codes automatically can significantly help reduce costs, and eliminate human biases and errors. However, unavailability of labeled datasets as well as the need for high precision results within the financial domain makes this a challenging problem. In this work, we propose a hierarchical multi-class industry code classifier with a targeted multi-label product/service code classifier leveraging advances in unsupervised representation learning techniques. We demonstrate how a high quality industry and product/service code classification system can be built using extremely limited labeled dataset. We evaluate our approach on a dataset of more than 20,000 companies and achieved a classification accuracy of more than 92\%. Additionally, we also compared our approach with a dataset of 350 manually labeled product/service codes provided by Subject Matter Experts (SMEs) and obtained an accuracy of more than 96\% resulting in real-life adoption within the financial domain.
In this paper, we employ spatial econometric methods to analyze panel data from German NUTS 3 regions. Our goal is to gain a deeper understanding of the significance and interdependence of industry clusters in shaping the dynamics of GDP. To achieve a more nuanced spatial differentiation, we introduce indicator matrices for each industry sector which allows for extending the spatial Durbin model to a new version of it. This approach is essential due to both the economic importance of these sectors and the potential issue of omitted variables. Failing to account for industry sectors can lead to omitted variable bias and estimation problems. To assess the effects of the major industry sectors, we incorporate eight distinct branches of industry into our analysis. According to prevailing economic theory, these clusters should have a positive impact on the regions they are associated with. Our findings indeed reveal highly significant impacts, which can be either positive or negative, of specific sectors on local GDP growth. Spatially, we observe that direct and indirect effects can exhibit opposite signs, indicative of heightened competitiveness within and between industry sectors. Therefore, we recommend that industry sectors should be taken into consideration when conducting spatial analysis of GDP. Doing so allows for a more comprehensive understanding of the economic dynamics at play.
Bram van den Akker, Olivier Jeunen, Ying Li
et al.
The bandit paradigm provides a unified modeling framework for problems that require decision-making under uncertainty. Because many business metrics can be viewed as rewards (a.k.a. utilities) that result from actions, bandit algorithms have seen a large and growing interest from industrial applications, such as search, recommendation and advertising. Indeed, with the bandit lens comes the promise of direct optimisation for the metrics we care about. Nevertheless, the road to successfully applying bandits in production is not an easy one. Even when the action space and rewards are well-defined, practitioners still need to make decisions regarding multi-arm or contextual approaches, on- or off-policy setups, delayed or immediate feedback, myopic or long-term optimisation, etc. To make matters worse, industrial platforms typically give rise to large action spaces in which existing approaches tend to break down. The research literature on these topics is broad and vast, but this can overwhelm practitioners, whose primary aim is to solve practical problems, and therefore need to decide on a specific instantiation or approach for each project. This tutorial will take a step towards filling that gap between the theory and practice of bandits. Our goal is to present a unified overview of the field and its existing terminology, concepts and algorithms -- with a focus on problems relevant to industry. We hope our industrial perspective will help future practitioners who wish to leverage the bandit paradigm for their application.
With the growing competition in banking industry, banks are required to follow customer retention strategies while they are trying to increase their market share by acquiring new customers. This study compares the performance of six supervised classification techniques to suggest an efficient model to predict customer churn in banking industry, given 10 demographic and personal attributes from 10000 customers of European banks. The effect of feature selection, class imbalance, and outliers will be discussed for ANN and random forest as the two competing models. As shown, unlike random forest, ANN does not reveal any serious concern regarding overfitting and is also robust to noise. Therefore, ANN structure with five nodes in a single hidden layer is recognized as the best performing classifier.
Cabe preguntarse si se puede hablar de novedad en las condiciones generales impuestas a la arquitectura en nuestros días o si se trata de una cierta vuelta a los orígenes, acaso un regreso cíclico: las limitaciones dictadas por la crisis climática a la industria de la construcción o la optimización de las relaciones con el medio natural se antojan como un dictado atemporal en la buena arquitectura desde siempre.
Así estos enunciados se encuentran presentes en la obra de muchos autores del pasado –remoto y reciente– cuya obra nos ilumina todavía hoy. De aquí la conveniencia de revisitar determinados ejemplos que han demostrado su pertinencia de partida y el éxito en su devenir.
En España las necesidades y las limitaciones derivadas del período autárquico que siguió a la Guerra Civil impusieron la lógica natural de la adaptación. Y más en determinados entornos y programas dictados desde la modestia. Este es el caso del Instituto Tajamar en Vallecas (Madrid), obra de los arquitectos César Ortiz- Echagüe y Rafael Echaide.
En esta obra, desarrollada al final de su colaboración en común, se produjo un cambio de paradigma en su arquitectura: del sueño miesiano que caracterizó la mayor parte de su obra a lo que podríamos llamar un pragmatismo poético inspirado en la arquitectura de Richard Neutra a quien Ortiz-Echagüe había tratado y acompañado durante su visita a España en 1954.
Abstract
One may wonder whether the term novelty encompasses the general conditions applied to architecture these days or whether it is rather a return to the origins, perhaps a cyclical regression: the restrictions imposed on the construction industry as a consequence of the climate crisis or of optimizing the relationship with the natural environment seem to be a timeless dictate always present in good architecture.
These statements are found in the works of many authors from the distant and recent past that still inspire us today; hence, the interest of re-examining certain examples that have proved their initial relevance and their successful evolution.
In Spain, the needs and limitations arising from the autarchic period following the Civil War imposed the natural logic of adaptation, and more so in certain settings and programs in which modesty prevails. This is the case of Instituto Tajamar in Vallecas (Madrid), designed by the architects César Ortiz-Echagüe and Rafael Echaide.
Ortiz-Echagüe and Echaide completed this project at the end of their collaboration, and it meant a paradigm shift in their architecture: from the Miesian dream that characterized most of their work to what could be termed a poetic pragmatism inspired by the architecture of Richard Neutra, whom Ortiz-Echagüe had met and accompanied during his visit to Spain in 1954.
The process of employing modern technology in a consistent manner is what the researcher is interested in, and the psychological role of the sound effect in enhancing psychopathic representations in cinematic characters, which had a wide resonance in the field of cinematic films, and after the predominance of digital technology in the production of contemporary films, the sound effect has a higher efficiency And a good level of advanced aesthetic and dramatic expression in film employment, so many directors resorted to this type of films by using various new and advanced techniques and technological programs in their industry, since the traditional construction does not achieve the dazzling that the viewer desires.
Accordingly, the researcher found that it is necessary to shed light on this topic due to its importance and research in it, so a title was chosen for it (the role of the sound effect to represent the psychopathic personality in the cinema), to include the methodological framework, defining the problem, its importance and the need for it, and defining the terms (sound effect, personality Psychopathy), and the theoretical framework included the first topic (the sound effect’s significance and concept),the second topic (the psychological dimension of the psychopathic personality in the cinema), and the third topic (the psychopathic personality from the sound semantics in the cinema), after that the researcher came out with a set of indicators that he adopted as tools for analyzing the sample And the framework concluded with previous studies.
The analytical descriptive approach took its approach, and an intentional sample that meets the research objectives, the American movie (Schizophrenia SPILT), directed by M. Night Shyamalan, produced in 2016, and the researcher relied on the indicators provided for the theoretical framework to analyze the sample, and took the scene as a main analysis unit in the research, and it was produced the study a number of results and conclusions, then conclude the research with a list of sources and appendices
Mahya Karimzadeh khosroshahi, Mohammad Ebrahim Aghababaei
In the past few years, several major domestics and international challenges have emerged, causing global political and economic uncertainty. Economic uncertainty, defined as the difficulty in predicting the economic environment, arises from various factors such as political instability, changes and uncertainties in government policies, natural disasters, and market fluctuations. The presence of such uncertainties significantly affects the efficiency of markets, including the efficiency of the capital market. The aim of this study is to examine the long-term relationship between of economic policies uncertainty (based on the fluctuations of macroeconomic variables using the composite PCA index) and the excess return of eight different industries index (Automobile and parts manufacturing, Pharmaceutical Products and Materials , cement, lime and gypsum, Multidisciplinary industrial companies , basic metals, oil, coke, and nuclear fuel, coke and nuclear fuels, chemical products, Aggregation, properties and real estate).The investigation, conducted using the econometric ARDL approach over the period from 2012 to 2021, demonstrates that economic policies uncertainty is positively and significantly related to the excess returns of the selected industry index Among the various industries, the Automobile and manufacturing parts industry is most affected by the of economic policies uncertainty, while the construction and real estate industry is least affected. Furthermore, the speed of adjustment of Aggregation, properties and real estate the effect of Economic policy uncertainty on the excess returns of the stock market industries is not homogeneous, as indicated by the ECM coefficient. Automobile and manufacturing parts industry index experiences the fastest adjustment, while the Multidisciplinary industrial companies, due to their diverse portfolios, exhibit the slowest adjustment speed compared to others..