Hasil untuk "Construction industry"

Kushal Chawla, Chenyang Zhu, Pengshan Cai et al.

Summarization of multi-party dialogues is a critical capability in industry, enhancing knowledge transfer and operational effectiveness across many domains. However, automatically generating high-quality summaries is challenging, as the ideal summary must satisfy a set of complex, multi-faceted requirements. While summarization has received immense attention in research, prior work has primarily utilized static datasets and benchmarks, a condition rare in practical scenarios where requirements inevitably evolve. In this work, we present an industry case study on developing an agentic system to summarize multi-party interactions. We share practical insights spanning the full development lifecycle to guide practitioners in building reliable, adaptable summarization systems, as well as to inform future research, covering: 1) robust methods for evaluation despite evolving requirements and task subjectivity, 2) component-wise optimization enabled by the task decomposition inherent in an agentic architecture, 3) the impact of upstream data bottlenecks, and 4) the realities of vendor lock-in due to the poor transferability of LLM prompts.

Puyu Zeng, Zhaoxi Wang, Zhixu Duan et al.

Code generation and comprehension by Large Language Models (LLMs) have emerged as core drivers of industrial intelligence and decision optimization, finding widespread application in fields such as finance, automation, and aerospace. Although recent advancements have demonstrated the remarkable potential of LLMs in general code generation, existing benchmarks are mainly confined to single domains and languages. Consequently, they fail to effectively evaluate the generalization capabilities required for real-world industrial applications or to reflect the coding proficiency demanded by complex industrial scenarios. To bridge this gap, we introduce IndustryCode, the first comprehensive benchmark designed to span multiple industrial domains and programming languages. IndustryCode comprises 579 sub-problems derived from 125 primary industrial challenges, accompanied by rigorous problem descriptions and test cases. It covers a wide range of fields, including finance, automation, aerospace, and remote sensing-and incorporates diverse programming languages such as MATLAB, Python, C++, and Stata. In our evaluation, the top-performing model, Claude 4.5 Opus, achieved an overall accuracy of 68.1% on sub-problems and 42.5% main problems. The benchmark dataset and automated evaluation code will be made publicly available upon acceptance.

Rituraj Singh, Sachin Pawar, Girish Palshikar

Commonsense knowledge bases (KB) are a source of specialized knowledge that is widely used to improve machine learning applications. However, even for a large KB such as ConceptNet, capturing explicit knowledge from each industry domain is challenging. For example, only a few samples of general {\em tasks} performed by various industries are available in ConceptNet. Here, a task is a well-defined knowledge-based volitional action to achieve a particular goal. In this paper, we aim to fill this gap and present a weakly-supervised framework to augment commonsense KB with tasks carried out by various industry groups (IG). We attempt to {\em match} each task with one or more suitable IGs by training a neural model to learn task-IG affinity and apply clustering to select the top-k tasks per IG. We extract a total of 2339 triples of the form $\langle IG, is~capable~of, task \rangle$ from two publicly available news datasets for 24 IGs with the precision of 0.86. This validates the reliability of the extracted task-IG pairs that can be directly added to existing KBs.

Ray Wai Man Kong, Ding Ning, Theodore Ho Tin Kong

This article presents applied research on line balancing within the modern garment industry, focusing on the significant impact of intelligent hanger systems and hanger lines on the stitching process, by Lean Methodology for garment modernization. It explores the application of line balancing in the modern garment industry, focusing on the significant impact of intelligent hanger systems and hanger lines on the stitching process. It aligns with Lean Methodology principles for garment modernization. Without the implementation of line balancing technology, the garment manufacturing process using hanger systems cannot improve output rates. The case study demonstrates that implementing intelligent line balancing in a straightforward practical setup facilitates lean practices combined with a digitalization system and automaton. This approach illustrates how to enhance output and reduce accumulated work in progress.

Sugiri Sugiri, Mochamad Bruri Triyono, Yosef Budiman et al.

Modern automotive design has increasingly embraced plastics for bumper construction; however, it can lead to material degradation. To overcome these limitations, the automotive industry is turning to fiber–resin material, namely carbon–epoxy composites. Our research focuses on determining the effects of fiber orientation and angle alignment on the structural stress of the car bumper, examining the hybrid material (carbon–epoxy reinforced by CFRP) in static structural tests, and performing dynamic impact tests at various speeds, applying the Tsai–Wu criterion as a basic failure model. However, Tsai–Wu’s failure in numerical analysis highlights the limitation of not being able to experimentally distinguish between failure modes and their interaction coefficients. To address this issue, we employ ANSYS^® 2024 R1 with a Fortran program, which enables more accurate estimation of failure behavior, resulting in an average error of 13.19%. To identify research gaps, machine learning (ML) plays a vital role in predicting parameter values and assessing data normality using various algorithms. By combining ML and FEA simulations, the result shows strong data performance. Bridging from 2 mm mesh sizing of 50% carbon–epoxy woven/50% CFRP laminate in 6 mm thickness at 0° orientation shows the most distributed shear stresses and deformation, which converged toward stable values. For comprehensive research, total deformation was included in ML analysis as a second target to build a multivariate analysis. Overall, Random Forest (RF) is the best-performing model, indicating superior robustness for modeling shear stress and total deformation.

Duihong Zhang, Ruoxi Wang, Xin Ouyang et al.

Carbon Capture, Utilization and Storage (CCUS) is an important strategic reserve technology to reduce CO2 emissions. Accelerating the application and development of CCUS technology is a realistic need and an important path for the energy industry to achieve the goal of carbon peak and carbon neutrality. It is the most economical method to transport CO2 from carbon source to carbon sink in supercritical state through pipeline. The key issue of supercritical/dense phase CO2 pipeline design is whether the pipeline steel has an adequate toughness to arrest running ductile fracture. For the study of toughness requirements of pipeline, full-scale burst test is the most direct and effective method at present. In order to research the toughness requirements of the supercritical CO2 pipeline, the first full-scale burst test of CO2 pipeline in China was carried out. The X65 steel pipeline with an outer diameter of 323.9 mm and a wall thickness of 7.2–7.6 mm was used as the test pipe. The test gas was 95% CO2 + 4% N2 + 1% H2, the test pressure was 11.85 MPa, and the temperature was 12.6 °C. The test results show that the axial prefabricated crack of the crack initiation pipe was successfully detonated and the crack propagated along the axial direction. On the west side, the crack was arrested at the girth weld of the two pipelines, and on the east side the crack was arrested ductilely because the base metal of the pipeline had sufficient toughness. The test steel pipe showed typical ductile shear fracture characteristics. The data of crack propagation velocity, pressure and temperature were collected, and the test results were accurate. After the burst of the pipe, the high-pressure gas in the pipe was sprayed upward and out in the opposite direction of the wind direction, and then diffused along the wind direction to the external field under the action of the wind velocity. This test provides data support for China to master the development, pipeline design and construction technology of million-ton CO2 pipeline. The test results will significantly improve the prediction accuracy of crack arrest toughness of CO2 pipeline of China, and provide important technical support for the safe construction and operation of global CO2 pipeline.

Abdul Jabbar Khan, Ling Gao, Yi Zhang et al.

Silicon-based solid-state batteries (Si-SSBs) are now a leading trend in energy storage technology, offering greater energy density and enhanced safety than traditional lithium-ion batteries. This review addresses the complex challenges and recent progress in Si-SSBs, with a focus on Si anodes and battery manufacturing methods. It critically analyzes the lithiation process in Si anodes, emphasizing the significant volumetric expansion and evolving solid-electrolyte interphase (SEI), both of which are crucial for the electrochemical performance and durability of batteries. Innovations in anode design, such as morphological optimization and compositional alloying, have been explored to reduce mechanical stress and improve the electrochemical properties. Moreover, we elaborate in detail the essential steps in the layer-by-layer construction and encapsulation of Si-SSBs, which are vital for their stability and function. Finally, this review offers a thorough examination of present scientific and technological developments, providing insights and prospective pathways for researchers and industry professionals dedicated to advancing SSB technology.

LIU Changxi, QI Guomin, WANG Jicheng, LI Tianye, YANG Jian, LEI Xia

To promote the process of carbon emission reduction in the electric power industry and achieve the goal of “carbon peaking and carbon neutrality”, the construction of a unified national power market system is being accelerated. A two-stage market clearing model considering load participation in carbon trading is proposed to reduce carbon emissions and facilitate clean energy substitution in the electricity sector. First, an initial carbon quota allocation method for thermal power units based on zero sum gains-data envelopment analysis is introduced, and the electricity market clearing model considering carbon trading is established. Then, based on the market clearing results from the first stage, the new energy consumption of loads is determined using the power flow tracing theory, and the Chinese certified emission reduction (CCER) is calculated. Following CCER carbon offset rules, the second stage of carbon emission trading is initiated, and the secondary electricity market subject to carbon emission constraints, is cleared based on the carbon trading results. Finally, an analysis using the improved IEEE 30-bus system is conducted to validate the effectiveness of the proposed market model. The results show that the proposed model not only helps reduce the carbon emissions from thermal power units but also increases the market share of new energy consumption and lowers average electricity prices. Additionly, the model provides a viable scheme for the large-scale marketization consumption of new energy.

Zhou Zhenquan, Kou Yuping, Fan Xiang et al.

It is widely agreed that the Industry 4.0 period has been a key promoter of facilitating the digital transformation of global industries, leading to more efficient ways of working. The construction industry is recognised as a significant contributor to the impact of energy use and carbon emissions, which are relevant to global warming and related correlational risks. Based on this situation, many scholars support the sustainable transformation of the building sector by promoting modular construction projects, which represent an innovative approach to building. However, attitudinal resistance from some stakeholders still needs to be improved in order to increase the use of modular constructions, which is not a positive signal for the current sustainable development strategy. This paper presents a comprehensive analysis of the key benefits of using prefabricated constructions, drawing on a thorough literature review and comparative analysis. It finds that developing and developed countries have gradually accepted this off-site construction method, and the stakeholder support significantly facilitates its effective promotion. Meanwhile, enhancements in construction management effectiveness, improvements in building safety, and contributions to project sustainability modification are several major motivations for employing this innovative approach in building project development. The analytical findings can facilitate the widespread adoption of prefabricated constructions, thereby enhancing environmental performance and contributing to the sustainable development of the building sector in various regions. Further research should consider reducing subjectivity in collated viewpoints by employing the multi-criterion analysis method.

Zhen Yu, Feiwen Wang, Long Ye et al.

In today’s rapidly evolving organizations, talent management plays a critical role in driving sustainable growth. Talents, particularly those exhibiting leadership potential, are often seen as essential assets for organizational development. However, the presence of high employee’s leadership potential can also generate adverse emotional reactions from leaders, potentially leading to behaviors such as leader jealousy and leader ostracism. This study investigates the dark side of employee’s leadership potential by examining the mechanisms through which employee’s leadership potential influences leader ostracism, with leader jealousy acting as a mediator. Drawing on social comparison theory, we propose a theoretical model that includes organizational competitive climate and leader’s core self-evaluation as moderating factors. Using a three-wave survey of 672 leaders in the Chinese construction industry, hierarchical regression analysis was employed to test the hypotheses. The results show that employee’s leadership potential significantly increases both leader jealousy and leader ostracism, with leader jealousy serving as a mediator. Moreover, a high organizational competitive climate strengthens the relationship between employee’s leadership potential and leader jealousy, thereby enhancing the entire mediated effect. In contrast, high leader core self-evaluation weakens the relationship between employee’s leadership potential and leader jealousy, reducing the likelihood of leader ostracism and attenuating the mediated effect. This study provides both theoretical contributions and practical insights for organizations seeking to manage high-leadership potential employees while minimizing the risk of negative leadership behaviors.

Surya N Reddy, Vaibhav Kurrey, Mayank Nagar et al.

Proper use of personal protective equipment (PPE) can save the lives of industry workers and it is a widely used application of computer vision in the large manufacturing industries. However, most of the applications deployed generate a lot of false alarms (violations) because they tend to generalize the requirements of PPE across the industry and tasks. The key to resolving this issue is to understand the action being performed by the worker and customize the inference for the specific PPE requirements of that action. In this paper, we propose a system that employs activity recognition models to first understand the action being performed and then use object detection techniques to check for violations. This leads to a 23% improvement in the F1-score compared to the PPE-based approach on our test dataset of 109 videos.

Ashok Urlana, Charaka Vinayak Kumar, Ajeet Kumar Singh et al.

Large language models (LLMs) have become the secret ingredient driving numerous industrial applications, showcasing their remarkable versatility across a diverse spectrum of tasks. From natural language processing and sentiment analysis to content generation and personalized recommendations, their unparalleled adaptability has facilitated widespread adoption across industries. This transformative shift driven by LLMs underscores the need to explore the underlying associated challenges and avenues for enhancement in their utilization. In this paper, our objective is to unravel and evaluate the obstacles and opportunities inherent in leveraging LLMs within an industrial context. To this end, we conduct a survey involving a group of industry practitioners, develop four research questions derived from the insights gathered, and examine 68 industry papers to address these questions and derive meaningful conclusions. We maintain the Github repository with the most recent papers in the field.

Ghalib Ahmed Tahir, Murtaza Ashraf

Employee turnover remains a pressing issue within high-tech sectors such as IT firms and research centers, where organizational success heavily relies on the skills of their workforce. Intense competition and a scarcity of skilled professionals in the industry contribute to a perpetual demand for highly qualified employees, posing challenges for organizations to retain talent. While numerous studies have explored various factors affecting employee turnover in these industries, their focus often remains on overarching trends rather than specific organizational contexts. In particular, within the software industry, where projectspecific risks can significantly impact project success and timely delivery, understanding their influence on job satisfaction and turnover intentions is crucial. This study aims to investigate the influence of project risks in the IT industry on job satisfaction and employee turnover intentions. Furthermore, it examines the role of both external and internal social links in shaping perceptions of job satisfaction.

Alessandro Massaad, Rene Moawad, Oumaima Nijad Fares et al.

We revisit the long-only trend-following strategy presented in A Century of Profitable Industry Trends by Zarattini and Antonacci, which achieved exceptional historical performance with an 18.2% annualized return and a Sharpe Ratio of 1.39. While the results outperformed benchmarks, practical implementation raises concerns about robustness and evolving market conditions. This study explores modifications addressing reliance on T-bills, alternative fallback allocations, and industry exclusions. Despite attempts to enhance adaptability through momentum signals, parameter optimization, and Walk-Forward Analysis, results reveal persistent challenges. The results highlight challenges in adapting historical strategies to modern markets and offer insights for future trend-following frameworks.

Muhammad Yasir Siddiqui, Alam Gir

The e-commerce systems are being tackled from commerce behavior and internet technologies. Therefore, trust aspect between buyer-seller transactions is a potential element which needs to be addressed in competitive e-commerce industry. The e-commerce industry is currently handling two different trust approaches. First approach consists on centralized mechanism where digital credentials/set of rules assembled, called Policy based trust mechanisms . Second approach consists on decentralized trust mechanisms where reputation, points assembled and shared, called Reputation based trust mechanisms. The difference between reputation and policy based trust mechanism will be analyzed and recommendations would be proposed to increase trust between buyer and seller in e-commerce industry. The integration of trust mechanism is proposed through mapping process, strength of one mechanism with the weakness of other. The proposed model for integrated mechanism will be presented and illustrated how the proposed model will be used in real world e-commerce industry.

Duraj Miloš, Niemiec Dominik, Kubáč Jan et al.

Today’s appearance of spa towns in the country is represented by the architecture of the 19th and 20th centuries. We mainly find elements of empire, neo-renaissance, and art nouveau in them. Even Karlovy Vary, even though its history goes back to the past, presents itself with this architecture. Even though the spa was here at the very beginning of the city’s foundation, nothing was left of the original buildings due to natural disasters. If they were not natural disasters, they were also remediation that freed up space for the construction of new buildings. Apart from hotel buildings, typical objects of spa architecture are mainly spa buildings and pavilions, construction modifications of springs or colonnades. An essential part of these centres is also greenery and water supplements that balance the mass of these buildings. However, the favourable geological, especially hydrogeological and geomorphological conditions of these locations play the most important role for the development of the spa industry. From the point of view of tourism in Karlovy Vary, the aim of this work is to connect the classic spa tourism of this city, which was already supplemented by film tourism in the middle of the 20th century with geotourism.

Pengcheng Pan, Maoyuan Li, Chenshuo Li et al.

Building information modelling (BIM) technology, which has experienced rapid development, has become the focus of digital education learning in architecture, engineering, and construction (AEC) related disciplines. However, BIM education is still confronted with the disconnection between theoretical education and engineering practice. In mainland China, BIM competitions are an important digital platform for higher education practice teaching. As the organizer and leader of student participants, BIM instructors, especially their BIM capability, have an important impact on digital education. Previous research on BIM capability did not involve the field of BIM education, and the existing BIM capability framework is not entirely applicable to evaluating the BIM capability of instructors. Semi-structured interviews based on grounded theory (GT) and structural equation modeling (SEM) were used to construct a five-dimensional model containing 23 capability indicators. The research findings highlighted the multi-dimensional nature of BIM capability for instructors and indicated that personnel capability was the most important for instructors, while process capability was considered the most dispensable. This is significantly different from the emphasis on technical and process capability in BIM capability research in the traditional AEC industry. It was also found that students from different levels of universities and different educational backgrounds had different demands for the BIM capability of instructors. The results of this study will help universities select excellent instructors, improve the quality of BIM education in universities, and cultivate more outstanding BIM talents for the development of BIM in the AEC industry, thereby promoting the digital practice of BIM education in universities.

Hui Liu, Kangqi Xu, Huimin Wang et al.

ABSTRACT: The aim of this study was to investigate the effects of low-protein diets and the sustained release of synthetic amino acids (AA) on the performance, intestinal barrier function and nitrogen excretion of laying hens. Two hundred eighty-eight 39-week-old Hyline brown laying hens of were randomly divided into 3 groups with 8 replicates per group. The crude protein level in the control group (CON) was 16%, the crude protein levels in the crystal AA supplement group (LCP-CAA) and microencapsulated AA group (LCP-MAA) were both 13%, and the AA levels in the LCP-CAA and LCP-MAA groups were consistent with that in the CON group. The experiment lasted 12 wk, and production performance was assessed weekly. The FCR and ADFI values were significantly greater for the LCP-CAA group than for the CON and LCP-MAA groups (P < 0.05). Two hours after feeding, His levels were significantly greater in the LCP-CAA group than in the LCP-MAA group (P < 0.05); 4 h after feeding, the contents of Met, Thr, Leu and Val were significantly greater in blood from the LCP-MAA group (P < 0.05); 6 h after feeding, Trp, Ile and Arg levels were significantly greater in the LCP-MAA group (P < 0.05). The chylase content significantly decreased in the duodenum of the LCP-CAA group (P < 0.05), and the chylase and trypsin were contents increased in the ileum of the LCP-MAA group (P < 0.05). In the LCP-MAA group, significantly increased mRNA expression levels of Occludin, ZO-1 in duodenum; Occludin, ZO-1, y+LAT1 in jejunum; and ZO-1 in ileum were detected at 8 and 12 weeks (P < 0.05). The fecal nitrogen content significantly decreased in the low protein diet group (P < 0.01). In conclusion, reducing dietary crude protein levels and supplementing with microencapsulated AAs can improve intestinal barrier function, promote digestive enzyme secretion, increase the expression of AA transporters, improve dietary protein utilization efficiency, and reduce nitrogen emission in laying hens.

Faheem Vahed, Mochelo Lefoka, Abimbola Windapo

Mindy Tran, Yasemin Acar, Michel Cucker et al.

Recent years have shown increased cyber attacks targeting less secure elements in the software supply chain and causing fatal damage to businesses and organizations. Past well-known examples of software supply chain attacks are the SolarWinds or log4j incidents that have affected thousands of customers and businesses. The US government and industry are equally interested in enhancing software supply chain security. We conducted six panel discussions with a diverse set of 19 practitioners from industry. We asked them open-ended questions regarding SBOMs, vulnerable dependencies, malicious commits, build and deploy, the Executive Order, and standards compliance. The goal of this summit was to enable open discussions, mutual sharing, and shedding light on common challenges that industry practitioners with practical experience face when securing their software supply chain. This paper summarizes the summit held on September 30, 2022.