Cyber-Physical Systems (CPS) play a critical role in modern industrial domains, including manufacturing, energy, transportation, and healthcare, where they enable automation, optimization, and real-time decision-making. Ensuring the robustness of these systems is paramount, as failures can have significant economic, operational, and safety consequences. This paper present findings from an industrial survey conducted in Wallonia, covering a wide range of sectors, to assess the current state of practice in CPS robustness. It investigates robustness from how it is understood and applied in relationship with requirements engineering, system design, test execution, failure modes, and available tools. It identifies key challenges and gaps between industry practices and state-of-the-art methodologies. Additionally, it compares our findings with similar industrial surveys from the literature.
As hardware design complexity increases, hardware fuzzing emerges as a promising tool for automating the verification process. However, a significant gap still exists before it can be applied in industry. This paper aims to summarize the current progress of hardware fuzzing from an industry-use perspective and propose solutions to bridge the gap between hardware fuzzing and industrial verification. First, we review recent hardware fuzzing methods and analyze their compatibilities with industrial verification. We establish criteria to assess whether a hardware fuzzing approach is compatible. Second, we examine whether current verification tools can efficiently support hardware fuzzing. We identify the bottlenecks in hardware fuzzing performance caused by insufficient support from the industrial environment. To overcome the bottlenecks, we propose a prototype, HwFuzzEnv, providing the necessary support for hardware fuzzing. With this prototype, the previous hardware fuzzing method can achieve a several hundred times speedup in industrial settings. Our work could serve as a reference for EDA companies, encouraging them to enhance their tools to support hardware fuzzing efficiently in industrial verification.
Iva Kertusha, Gebremariem Assress, Onur Duman
et al.
Web application testing is an essential practice to ensure the reliability, security, and performance of web systems in an increasingly digital world. This paper presents a systematic literature survey focusing on web testing methodologies, tools, and trends from 2014 to 2025. By analyzing 259 research papers, the survey identifies key trends, demographics, contributions, tools, challenges, and innovations in this domain. In addition, the survey analyzes the experimental setups adopted by the studies, including the number of participants involved and the outcomes of the experiments. Our results show that web testing research has been highly active, with ICST as the leading venue. Most studies focus on novel techniques, emphasizing automation in black-box testing. Selenium is the most widely used tool, while industrial adoption and human studies remain comparatively limited. The findings provide a detailed overview of trends, advancements, and challenges in web testing research, the evolution of automated testing methods, the role of artificial intelligence in test case generation, and gaps in current research. Special attention was given to the level of collaboration and engagement with the industry. A positive trend in using industrial systems is observed, though many tools lack open-source availability
Despite decades of study, a quantitative, integrated framework to evaluate minutescale throughput, geometric control, and a zero external footprint for Khufu's pyramid has been lacking. We test the Integrated Edge-Ramp (IER) model-a helical path formed by omitting and backfilling perimeter courses-using a unified, end-to-end pipeline coupling parametric geometry, discrete-event logistics, and staged finite-element analysis (FEA). An adaptive multiramp strategy can sustain 4-6-minute dispatches and yields a median on-site duration of 13.8-20.6 years (95% CI); including quarrying, river transport, and seasonal pauses gives 20-27 years. FEA indicates that stresses and settlements remain within plausible limits for Old Kingdom limestone under self-weight. The model's geometry is also consistent with internal voids identified by muon imaging (a hypothesis-generating result). The IER helps reconcile throughput, survey access, and zero-footprint closure, and produces falsifiable predictions (edge-fill signatures, corner wear). Our study provides a transferable, open-data/code framework for testing construction hypotheses for ancient megastructures.
Benjamin Neale, Sakdirat Kaewunruen, Dan Li
et al.
This study aims to define specific transferable engineering capabilities needed for the implementation (design and practices) of circular economy (CE) within a smart city setting. We conducted a critical literature review of over 100 studies on the core values of CE and smart cities to investigate the knowledge gap in this topic and understand what specific skillset is employed by industry experts that can be harnessed on a wider scale, which can allow for the optimization of CE. There is a lack of research on the skillsets needed to implement a circular economy in any setting, and there are very few studies on circularity practices in a smart city setting. Primary data collection allows us to bridge this knowledge gap, yielding new findings that do not already exist concerning the skillset employed by experts in the field, which can positively impact the smart city settings in which a circular economy is implemented. We conducted a qualitative analysis based on expert interviews of 21 participants who have experience in the circular economy. This information will benefit the industry by informing businesses and councils about the key skillsets and capabilities to look out for when employing people to implement any aspect of circular practices in a smart city setting, with an emphasis on enhancing efficiency, achieving deliverables, and thinking systemically to address complex challenges they may face during the implementation. We also investigated the implementation of CE in smart cities to provide a well-rounded view of the different achievements and challenges faced during the process. This mainly focuses on the work of governance in smart circular cities, a factor that has many important implications and externalities in different sectors. This study describes the methodology adopted to formulate a detailed questionnaire for expert interviews with respect to the skill gap and capabilities necessary for working in the industry, the results of which aid discussions regarding the different challenges faced in CE implementation. Our findings reveal that background knowledge in engineering and sustainability is the most ‘highly critical’ hard skill according to the experts, while communication and stakeholder engagement are the essential soft skills required to ensure the success of a circular economy within smart city settings.
Purpose: This research explores the effect of BIM adoption on project performance with the focus on the mediation of resource efficiency and the moderating factor of stakeholder work with each other. Through the combination of these essential aspects, the study will help to obtain a thorough insight into the possible ways of maximizing the use of resources, minimizing wastages, and enhancing the effectiveness of the construction projects with the use of BIM.
Design/Methodology/Approach: The study adopts a quantitative, cross-sectional survey design. The design is further enhanced by incorporating Hayes PROCESS Model 5, which enables simultaneous testing of mediation and moderation effects.
Findings: Using a sample of 170 construction professionals and Hayes PROCESS Model 5, the study found that BIM adoption significantly improves resource efficiency and that resource efficiency, in turn, significantly improves project performance. Resource efficiency fully mediates the BIM → performance relationship; stakeholder collaboration did not moderate the direct path in this analysis.
Implications/Originality/Value: The findings provide both theoretical refinement (process-mediated view of BIM) and concrete directions for practitioners and policymakers in developing economies like Pakistan. The results support a process-oriented view of BIM: BIM yields organizational capabilities (resource efficiency) that then drive performance. This empirical evidence strengthens RBV-type reasoning that treating BIM as a capability (or enabler of capabilities) is more insightful than viewing it as an isolated technological input. This study presents practical results through a quantitative analysis of how organizations can use BIM to achieve improved project deliverables. The result will add to both the academic literature and the industry practice in order to help stakeholders to achieve maximum benefits of implementing BIM.
In this paper, we use open-source tools to perform quantum resource estimation to assess the requirements for industry-relevant quantum computation. Our analysis uses the problem of industrial shift scheduling in manufacturing and the Quantum Industrial Shift Scheduling algorithm. We base our figures of merit on current technology, as well as theoretical high-fidelity scenarios for superconducting qubit platforms. We find that the execution time of gate and measurement operations determines the overall computational runtime more strongly than the system error rates. Moreover, achieving a quantum speedup would not only require low system error rates ($10^{-6}$ or better), but also measurement operations with an execution time below 10ns. This rules out the possibility of near-term quantum advantage for this use case, and suggests that significant technological or algorithmic progress will be needed before such an advantage can be achieved.
Gorbaneva Elena, Kosovtseva Ilona, Anisimova Nadezhda
et al.
In the construction industry, the potential for thermal energy savings is particularly significant due to the large share and considerable losses of this type of energy resource in the overall energy consumption balance of the sector, which defines the objective of this research. This article presents a methodology for determining total thermal losses through enclosing structures and associated heat and mass transfer to the environment, which are influenced by both geometric and thermophysical properties of building elements as well as climatic characteristics of the project's location. It has been identified that climatic data contain a substantial stochastic component. Therefore, technical and managerial decisions should be based on the deterministic part of climate information. The contribution of technical and technological solutions to enhancing energy efficiency is defined by the magnitude of thermal losses, climatic characteristics of the project implementation region, and local thermal energy prices. A software implementation of a hierarchical information model for energy conservation has been developed within a relational database framework, enabling automatic maintenance of data integrity and consistency during updates while facilitating interaction among diverse participants in the project life cycle.
Objectives: Anbar Governorate is witnessing a great development in construction industries, especially Fallujah District. This study aims to identify the importance of construction industries and the extensive use of their products. The number of construction industries facilities reached (114) facilities distributed throughout the district’s areas, and (1586) individuals working in these industries.Methodology: The current study adopted the analytical-deductive approach in order to provide the required data on the phenomena and delve into the surrounding conditions, and the deductive approach in addition to the field study of the current reality for the year 2022.Results: the results showed that the area includes a number of various construction industry facilities distributed across the district’s regions, employing (1586) individuals, and most of the production is consumed in Anbar Governorate, and the rest is exported to other governorates. The production components are very widely available in the governorate due to the availability of a large area and the many deposits present in it, especially with the availability of raw materials such as limestone, sand, gravel, capital, market, labor, energy sources, fuel, and transportation methods. Its products have been able to provide most of the building materials needed for all urban, economic, and infrastructure projects. These industries are linked to population growth and urban expansion.Conclusion: The number of construction industries in Fallujah District reached (114) factories in 2022, and the largest percentage was for private sector factories, while the public sector only has two factories out of the total construction industries in the district.in fourth place, then asphalt factories in the fifth stage, gravel crushing and sand screening factories in sixth place, Bork factories in seventh place, then black and white cement factories in the eighth stage, and the thermal brick factory in last place.
History of scholarship and learning. The humanities
An imbalance in urban development in China has become a contradiction. Points of Interest (POIs) serve as representations of the spatial distribution of urban functions. Analyzing POI spatial co-occurrence patterns can reveal the agglomeration patterns of urban functions across cities at different levels, providing insights into imbalances in urban development. Using POI data from 297 cities in China, the Word2vec model was employed to model the POI spatial co-occurrence patterns, allowing for the quantification of fine-granular urban functionality. Subsequently, the cities were clustered into five tiers representing different levels of development. An urban hierarchical disparity index and graph were introduced to examine variations in urban functions across different tiers. A significant correlation between POI spatial co-occurrence patterns and the GDP of cities at different levels was demonstrated. This study revealed a notable polarization trend characterized by the development of top-tier cities and lagging tail-end cities. Top-tier cities exhibit advantages in terms of their commercial environments, such as international banks, companies, and transportation facilities. Conversely, tail-end cities face deficiencies in urban infrastructure. It is crucial to coordinate resource allocation and establish sustainable development strategies that foster mutual support between the top-tier and tail-end cities.
Michael C. Okika, Andre Vermeulen, Jan-Harm C. Pretorius
Interface risks are inherent in every construction project from start to finish. Identifying and managing these risks effectively in every project phase is crucial for actualising project objectives. This paper shows a comprehensive framework showing several relationships between project stakeholders and how the interface risks between them that influence project execution are identified and managed for the overall construction project success. Firstly, a literature review on interfaces and interface risks and a discussion on how organisations managed interface risks were carried out, and secondly, the collection of quantitative data was conducted by means of structured online questionnaires. The sample consisted of 205 construction project professionals who were selected randomly. This group included individuals with various roles in the construction industry. The data were analysed using descriptive statistical methods, including factor analysis, reliability assessment, and calculations of frequencies and percentages. The results showed all the factors, work cultures, and organisational approaches that influence interface risk management and ways to identify and manage interface risks effectively. Effective stakeholder management is crucial for effective interface risk management since many interface risks are created by the numerous stakeholders involved in the project and the proposed frameworks will effectively mitigate the consequences and causes of interface risks. Effectively mitigating these risks involves effective stakeholder management, building information modelling volume strategy, and creating a virtual construction model during the construction phase; in addition, construction supply chain risks must be carefully identified during the interfaces establishment stages; interface risks must be carefully identified during the conceptualisation; and the planning, construction, and execution stages and standard methods and procedures must be defined to effectively identify and manage interface risks as the occur in the project lifecycle plus implementing the proposed risk mitigation frameworks.
Johnderson Nogueira de Carvalho, Felipe Rodrigues da Silva, Erick Giovani Sperandio Nascimento
The biopharmaceutical industry has specificities related to the optimization of its processes, the effectiveness of the maintenance of the productive park in the face of regulatory requirements. and current concepts of modern industry. Current research on the subject points to investments in the health area using the current tools and concepts of Industry 4.0 (I4.0) with the objective of a more assertive production, reduction of maintenance costs, reduction of operating risks, and minimization of equipment idle time. In this context, this study aims to characterize the current knowledge about the challenges of the biopharmaceutical industry in the application of prescriptive maintenance, which derives from predictive maintenance, in the context of I4.0. To achieve this, a systematic review of the literature was carried out in the scientific knowledge bases IEEE Xplore, Scopus, Web of Science, Science Direct, and Google Scholar, considering works such as Reviews, Article Research, and Conference Abstracts published between 2018 and 2023. The results obtained revealed that prescriptive maintenance offers opportunities for improvement in the production process, such as cost reduction and greater proximity to all actors in the areas of production, maintenance, quality, and management. The limitations presented in the literature include a reduced number of models, the lack of a clearer understanding of its construction, lack of applications directly linked to the biopharmaceutical industry, and lack of measurement of costs and implementation time of these models. There are significant advances in this area including the implementation of more elaborate algorithms used in artificial intelligence neural networks, the advancement of the use of decision support systems as well as the collection of data in a more structured and intelligent way. It is concluded that for the adoption of prescriptive maintenance in the pharmaceutical industry, issues such as the definition of data entry and analysis methods, interoperability between “shop floor” and corporate systems, as well as the integration of technologies existing in the world, must be considered for I4.0.
Felix Dobslaw, Kristian Angelin, Lena-Maria Öberg
et al.
We see an explosive global labour demand in the Software Industry, and higher education institutions play a crucial role in supplying the industry with professionals with relevant education. Existing literature identifies a gap between what software engineering education teaches students and what the software industry demands. Using our open-sourced Job Market AnalyseR (JMAR) text-analysis tool, we compared keywords from higher education course syllabi and job posts to investigate the knowledge gap from a technology-focused departure point. We present a trend analysis of technology in job posts over the past six years in Sweden. We found that demand for cloud and automation technology such as Kubernetes and Docker is rising in job ads but not that much in higher education syllabi. The language used in higher education syllabi and job ads differs where the former emphasizes concepts and the latter technologies more heavily. We discuss possible remedies to bridge this mismatch to draw further conclusions in future work, including calibrating JMAR to other industry-relevant aspects, including soft skills, software concepts, or new demographics.
Compositional data are contemporarily defined as positive vectors, the ratios among whose elements are of interest to the researcher. Financial statement analysis by means of accounting ratios a.k.a. financial ratios fulfils this definition to the letter. Compositional data analysis solves the major problems in statistical analysis of standard financial ratios at industry level, such as skewness, non-normality, non-linearity, outliers, and dependence of the results on the choice of which accounting figure goes to the numerator and to the denominator of the ratio. Despite this, compositional applications to financial statement analysis are still rare. In this article, we present some transformations within compositional data analysis that are particularly useful for financial statement analysis. We show how to compute industry or sub-industry means of standard financial ratios from a compositional perspective by means of geometric means. We show how to visualise firms in an industry with a compositional principal-component-analysis biplot; how to classify them into homogeneous financial performance profiles with compositional cluster analysis; and how to introduce financial ratios as variables in a statistical model, for instance to relate financial performance and firm characteristics with compositional regression models. We show an application to the accounting statements of Spanish wineries using the decomposition of return on equity by means of DuPont analysis, and a step-by-step tutorial to the compositional freeware CoDaPack.
Sequential recommenders have been widely used in industry due to their strength in modeling user preferences. While these models excel at learning a user's positive interests, less attention has been paid to learning from negative user feedback. Negative user feedback is an important lever of user control, and comes with an expectation that recommenders should respond quickly and reduce similar recommendations to the user. However, negative feedback signals are often ignored in the training objective of sequential retrieval models, which primarily aim at predicting positive user interactions. In this work, we incorporate explicit and implicit negative user feedback into the training objective of sequential recommenders in the retrieval stage using a "not-to-recommend" loss function that optimizes for the log-likelihood of not recommending items with negative feedback. We demonstrate the effectiveness of this approach using live experiments on a large-scale industrial recommender system. Furthermore, we address a challenge in measuring recommender responsiveness to negative feedback by developing a counterfactual simulation framework to compare recommender responses between different user actions, showing improved responsiveness from the modeling change.
In recent years, as projects have become more complex, their problems have become bigger, so achieving success in the project has become the most important concern of project managers. Since success depends on many factors and one of the most important factors is the project's human resources. In this study, we examine the development of human resources. On the other hand, considering that the construction industry is very wide, for more accuracy, the focus of this study is only on the building field. Therefore, the purpose of this article is to evaluate the importance and strategy of human resource development in construction companies in Tehran. be Therefore, we have reviewed relevant relevant articles to find out the importance of human resource development in the construction industry, and then 35 contracting companies in Tehran, which are active in the field of building construction, have been examined in the field of human resource development. The findings show that most of the studied contracting companies accept human resources as an important resource, but unfortunately, they do not have a comprehensive and executive plan for the development and training of their human resources
Construction industry, Engineering (General). Civil engineering (General)
With the ever-increasing growth of energy demand and costs, process monitoring of operational costs is of great importance for process industries. In this light, both financial budget management and local operational optimization supposed to be guaranteed properly. To achieve this goal, a support vector machine recursive feature elimination (SVM-RFE) method together with clustering algorithm was developed to extract features while serving as importance measurements of each input variable for the sequential prediction model construction. Then, the four variants of autoregressive and moving average (ARMA), i.e., ARMA with exogenous input (ARMAX) based on recursive least squares algorithm (RLS), ARMAX based on recursive extended least squares algorithm (RELS), nonlinear auto-regressive neural network (NARNN) and nonlinear auto-regressive neural network with exogenous input (NARXNN), were applied, respectively, to predict the costs incurred in the daily production for process industries. The methods were validated in the Benchmark Simulation Model No.2-P (BSM2-P) and a practical data set about steel industry energy consumption from an open access database (University of California, Irvine (UCI)), respectively. The nonlinear model, NARXNN, was validated to achieve better performance in terms of mean square error (MSE) and correlation coefficient (R), when used for multi-step prediction of the aforementioned datasets with strong nonlinear and coupled characteristics.
Farhan Lafta Rashid, Muhammad Asmail Eleiwi, Hayder I. Mohammed
et al.
Energy security refers to a country’s capacity to provide the energy resources essential to its wellbeing, including a reliable supply at an affordable costs. Economic growth and development cannot occur without access to reliable energy sources. Energy availability is a proxy for a country’s standard of living and a key factor in its economic development and technical progress. Solar power is the most reliable and cost-effective option when it comes to meeting the world’s energy needs. Solar-powered cooling systems are one example of how solar energy may be used in the real world. Solar-powered air conditioners have become more popular in recent years. The problems caused by our reliance on fossil fuels may be surmounted with the help of solar cooling systems that use solar collectors. Solar cooling systems may utilize low-grade solar energy, making them popular in the construction industry. Solar cooling systems powered by photovoltaic–thermal (PVT) collectors have been the subject of much research to improve the thermodynamic and economic performance of solar cooling systems. This research focuses on exploring the potential of solar-generated heat for use in cooling systems. This study will also examine the current challenges involved with using solar energy in cooling applications, as well as the possible benefits that may help pave the way for more research and greater employment of heat gain from the solar system in various cooling applications.
The high-quality development of the manufacturing industry is not only a requirement of industrial transformation and upgrading but also an internal task for the sustainable development of manufacturing enterprises. The high-quality development of the manufacturing industry is a process of multi-participation and dynamic evolution. To understand the evolution of the high-quality development of the manufacturing industry, an evolutionary game model composed of local governments, leading enterprises, and following enterprises is constructed. The evolution process and the influence of internal factors such as innovation capability, organization construction and industry resources on the evolution and stability strategy are analysed. MATLAB software is used to perform numerical simulations. The results show that (1) there are two possible evolutionary stability strategy (ESS) models in the game, namely, {active supervision, positive participation, positive participation} and {active supervision, negative participation, negative participation}; (2) when the initial probabilities of leading and following enterprises are all at low levels, increasing any one of the local government's initial probability, innovation capability, organization construction and industry resources can promote tripartite evolution towards {active supervision, positive participation, positive participation}; and (3) the convergence rate of leading enterprises and following enterprises evolving towards a positive participation strategy will increase slightly with an increase in local government's initial probability, innovation capability, organization construction, and industry resources when both are at middle initial probability levels. The final policy suggestions can be used to help all parties choose the optimal strategy and to achieve the high-quality development target of the manufacturing industry as soon as possible.