Hasil untuk "Engineering economy"

Dectot--Le Monnier de Gouville Esteban, Mohammad Hamdaqa, Moataz Chouchen

YARA has established itself as the de facto standard for "Detection as Code," enabling analysts and DevSecOps practitioners to define signatures for malware identification across the software supply chain. Despite its pervasive use, the open-source YARA ecosystem remains characterized by ad-hoc sharing and opaque quality. Practitioners currently rely on public repositories without empirical evidence regarding the ecosystem's structural characteristics, maintenance and diffusion dynamics, or operational reliability. We conducted a large-scale mixed-method study of 8.4 million rules mined from 1,853 GitHub repositories. Our pipeline integrates repository mining to map supply chain dynamics, static analysis to assess syntactic quality, and dynamic benchmarking against 4,026 malware and 2,000 goodware samples to measure operational effectiveness. We reveal a highly centralized structure where 10 authors drive 80% of rule adoption. The ecosystem functions as a "static supply chain": repositories show a median inactivity of 782 days and a median technical lag of 4.2 years. While static quality scores appear high (mean = 99.4/100), operational benchmarking uncovers significant noise (false positives) and low recall. Furthermore, coverage is heavily biased toward legacy threats (Ransomware), leaving modern initial access vectors (Loaders, Stealers) severely underrepresented. These findings expose a systemic "double penalty": defenders incur high performance overhead for decayed intelligence. We argue that public repositories function as raw data dumps rather than curated feeds, necessitating a paradigm shift from ad-hoc collection to rigorous rule engineering. We release our dataset and pipeline to support future data-driven curation tools.

Rem Sadykhov, Geoff Goodell, Philip Treleaven

In this paper, we analyse the impacts of exogenous and endogenous factors on wealth distribution in the Bitcoin token economy, where wealth distribution refers to the distribution of BTC between economic participants or groups of economic participants. The objective of the paper is to analyse the impact of economic policies on wealth distribution in the Bitcoin ecosystem. Different macroeconomic and microeconomic time series are used to eliminate noise in the wealth distribution time series, and the causality analysis is performed between Bitcoin Improvement Proposals (i.e., BIPs) and the cleaned wealth distribution data to reveal possible patterns in the impacts that the endogenous policies have on wealth distribution in token economies. Lastly, a structure for economic policy taxonomy in token economies is proposed where different the policy implementations are illustrated by existing BIPs. This approach highlights the actions available to the policy makers, as well as providing a technique for analysis of policy impacts in token economies and their categorization.

Arpan Chakraborty

This paper analyzes the macroeconomic consequences of military spending and militarization within a dynamic growth framework. Building on a Keynesian goods-market model, we examine how the allocation of government expenditure between civilian and military sectors affects capital accumulation and technological progress. Military spending generates opposing effects: it stimulates aggregate demand and may support innovation through defense-related research, but it also crowds out civilian investment and creates structural rigidities. We formalize these mechanisms in a stylized endogenous-growth model in which productivity depends on the degree of militarization, producing a non-linear relationship between the military burden and long-run growth. Calibrated simulations show that moderate levels of military spending can temporarily support growth, whereas excessive militarization reduces long-run development. We further illustrate the asymmetric growth costs of conflict using a simple two-country war simulation between an advanced economy and a sanctioned middle-income economy.

Qi Diao, Chengyue Xie, Yuchen Yin et al.

Aiming at the shortcomings of the gazelle optimization algorithm, such as the imbalance between exploration and exploitation and the insufficient information exchange within the population, this paper proposes a multi-strategy improved gazelle optimization algorithm (MSIGOA). To address these issues, MSIGOA proposes an iteration-based updating framework that switches between exploitation and exploration according to the optimization process, which effectively enhances the balance between local exploitation and global exploration in the optimization process and improves the convergence speed. Two adaptive parameter tuning strategies improve the applicability of the algorithm and promote a smoother optimization process. The dominant population-based restart strategy enhances the algorithms ability to escape from local optima and avoid its premature convergence. These enhancements significantly improve the exploration and exploitation capabilities of MSIGOA, bringing superior convergence and efficiency in dealing with complex problems. In this paper, the parameter sensitivity, strategy effectiveness, convergence and stability of the proposed method are evaluated on two benchmark test sets including CEC2017 and CEC2022. Test results and statistical tests show that MSIGOA outperforms basic GOA and other advanced algorithms. On the CEC2017 and CEC2022 test sets, the proportion of functions where MSIGOA is not worse than GOA is 92.2% and 83.3%, respectively, and the proportion of functions where MSIGOA is not worse than other algorithms is 88.57% and 87.5%, respectively. Finally, the extensibility of MSIGAO is further verified by several engineering design optimization problems.

Florian Felten, Gabriel Apaza, Gerhard Bräunlich et al.

Engineering design optimization seeks to automatically determine the shapes, topologies, or parameters of components that maximize performance under given conditions. This process often depends on physics-based simulations, which are difficult to install, computationally expensive, and require domain-specific expertise. To mitigate these challenges, we introduce EngiBench, the first open-source library and datasets spanning diverse domains for data-driven engineering design. EngiBench provides a unified API and a curated set of benchmarks -- covering aeronautics, heat conduction, photonics, and more -- that enable fair, reproducible comparisons of optimization and machine learning algorithms, such as generative or surrogate models. We also release EngiOpt, a companion library offering a collection of such algorithms compatible with the EngiBench interface. Both libraries are modular, letting users plug in novel algorithms or problems, automate end-to-end experiment workflows, and leverage built-in utilities for visualization, dataset generation, feasibility checks, and performance analysis. We demonstrate their versatility through experiments comparing state-of-the-art techniques across multiple engineering design problems, an undertaking that was previously prohibitively time-consuming to perform. Finally, we show that these problems pose significant challenges for standard machine learning methods due to highly sensitive and constrained design manifolds.

Xingang Guo, Yaxin Li, Xiangyi Kong et al.

Modern engineering, spanning electrical, mechanical, aerospace, civil, and computer disciplines, stands as a cornerstone of human civilization and the foundation of our society. However, engineering design poses a fundamentally different challenge for large language models (LLMs) compared with traditional textbook-style problem solving or factual question answering. Although existing benchmarks have driven progress in areas such as language understanding, code synthesis, and scientific problem solving, real-world engineering design demands the synthesis of domain knowledge, navigation of complex trade-offs, and management of the tedious processes that consume much of practicing engineers' time. Despite these shared challenges across engineering disciplines, no benchmark currently captures the unique demands of engineering design work. In this work, we introduce EngDesign, an Engineering Design benchmark that evaluates LLMs' abilities to perform practical design tasks across nine engineering domains. Unlike existing benchmarks that focus on factual recall or question answering, EngDesign uniquely emphasizes LLMs' ability to synthesize domain knowledge, reason under constraints, and generate functional, objective-oriented engineering designs. Each task in EngDesign represents a real-world engineering design problem, accompanied by a detailed task description specifying design goals, constraints, and performance requirements. EngDesign pioneers a simulation-based evaluation paradigm that moves beyond textbook knowledge to assess genuine engineering design capabilities and shifts evaluation from static answer checking to dynamic, simulation-driven functional verification, marking a crucial step toward realizing the vision of engineering Artificial General Intelligence (AGI).

Xiaobei Han, Tianxiang Liu, Yuliang Cai et al.

Crops in greenhouses located in cold climates are frequently affected by high relative humidity (RH). This study presents the design, testing, and analysis of a dehumidifier based on thermoelectric cooling. Thermoelectric dehumidifiers (TEDs) are capable of dehumidifying greenhouses in cold regions while recovering heat for indoor air heating. The design of a TED is based on the specific characteristics of thermoelectric coolers (TECs). A TED consists of a cabinet, four heat exchangers, a duct fan, a water pump, and auxiliary components. The TED performance was evaluated in a Chinese solar greenhouse (CSG) with a volume of approximately 160 m³. The input voltage of the TECs, fan airflow rate, and cold-side fin area affected the TED performance, with their influence varying in magnitude. The radar chart results show that the optimal operating parameters are as follows: a fan airflow rate of 300 m³/h, a TEC input voltage of 15 V, and a cold-side fin area of 0.15 m². With the TED running for 120 min under the optimal parameters, the RH in the CSG decreased by 25.5%, while the air temperature increased by 3.4 °C. The installation of the TED at the bottom of the CSG improved the growing environment of the crops, particularly in the vertical range between 0.2 m and 1.5 m height inside the greenhouse. These findings provide a valuable reference for applying thermoelectric cooling technology in the greenhouse field.

Tan Gürpinar, Mehmet Akif Gulum, Melanie Martinelli

Enterprises today face increasing threats from cyberattacks, supply chain disruptions, and systemic market risks, making the enhancement of organizational resilience through advanced risk management frameworks increasingly critical. Traditional approaches often struggle to balance data privacy, cross-organizational collaboration, and real-time adaptability. While distributed ledger technologies (DLTs) initially enabled cryptocurrencies, they have evolved into a foundational infrastructure for decentralized AI applications. This study investigates how decentralized AI techniques, particularly federated learning, can support joint risk management processes in enterprise networks. First, a comprehensive review of decentralized AI methods is conducted to identify approaches suitable for enterprise risk management. Next, expert interviews are used to contextualize these insights, highlighting practical considerations, organizational challenges, and adoption constraints. Building on the literature and expert feedback, a decentralized framework is developed to allow organizations to securely share risk-related insights while preserving data privacy and control over proprietary information. The framework is validated through a technical prototype, combining architectural design with empirical proof-of-concept experiments on federated learning benchmarks. Results demonstrate the feasibility of achieving near-centralized model accuracy under privacy constraints, while also highlighting communication and governance issues that need to be addressed in real-world deployments. The study presents a structured comparison of decentralized AI techniques and a validated concept for enhancing supply chain risk prediction, fraud detection, and operational continuity across enterprise networks.

Daniele Ferrara, Paolo Cicconi, Angelo Minotti et al.

The recent evolution of the space industry, commonly referred to as New Space, has changed the way space missions are conceived, developed, and executed. In contrast to traditional approaches, the current paradigm emphasizes accessibility, commercial competitiveness, and rapid and sustainable innovation. This study proposes a research methodology for selecting relevant literature to identify the key design drivers and associated enablers that characterize the New Space context from an engineering design perspective. These elements are then organized into three categories: the evolution of traditional drivers, emerging manufacturing and integration practices, and sustainability and technology independence. This categorization highlights their role and relevance, providing a baseline for the development of systems for New Space missions. The results are further contextualized within three major application domains, namely Low Earth Orbit (LEO) small satellite constellations, operations and servicing in space, and space exploration, to illustrate their practical role in engineering space systems. By linking high-level industry trends to concrete design choices, this work aims to support the early design phases of New Space innovative systems and promote a more integrated approach between strategic objectives and technical development.

Casey O. Barkan

It is widely assumed that increases in economic productivity necessarily lead to economic growth. In this paper, it is shown that this is not always the case. An idealized model of an economy is presented in which a new technology allows capital to be utilized autonomously without labor input. This is motivated by the possibility that advances in artificial intelligence (AI) will give rise to AI agents that act autonomously in the economy. The economic model involves a single profit-maximizing firm which is a monopolist in the product market and a monopsonist in the labor market. The new automation technology causes the firm to replace labor with capital in such a way that its profit increases while total production decreases. The model is not intended to capture the structure of a real economy, but rather to illustrate how basic economic mechanisms can give rise to counterintuitive and undesirable outcomes.

Hwang-Ju Jeon, Donghyeon Kim, Fabiano B. Scheufele et al.

Pyrochar (Biochar) produced from the thermochemical conversion of biomass has been widely used as a soil amendment to improve agricultural soil quality. Since polycyclic aromatic hydrocarbons (PAHs) can be produced in such processes, the occurrence of PAHs in pyrochars has been extensively studied, and standards such as the European Biochar Certificate (EBC) and International Biochar Initiative (IBI) contain limit values for biochars applied to soils. However, studies on PAH levels in hydrochars from hydrothermal processes, which can be an alternative to wet biomass are scarce. This study focuses on comparing the occurrence of 16 PAHs regulated by the US EPA in 22 char samples (including pyrochars from pyrolysis, hydrochars from hydrothermal carbonization, and, for the first time, hydrothermal humification) using an ultrasonic extraction method. Results showed that the sum of the 16 EPA PAHs in all samples was well below the requirements of the two standards, except for pyrochar produced at the farm scale. They ranged from 131 to 9358 µg·kg⁻¹ in the seven pyrochars and from not detected to 333 µg·kg⁻¹ for the fourteen hydrochars. Our findings indicate that hydrochar produced via hydrothermal methods exhibits much lower concentrations and is a safe option for soil amendment and environmental applications.

G Priyanka, N Gireesh, S Hemachandra

This paper investigated the performance of Vedic multipliers in a 32-bit Multiplier-Accumulator Unit (MAC) by comparing Urdhva Tiryakbhyam and Nikhilam Sutras with various adder architectures. The goal was to identify the optimal combination of speed and resource efficiency. Urdhva Tiryakbhyam with CLA emerged as the fastest option, achieving a minimal delay of 0.709 ns. However, this came at the cost of higher resource utilization, measured in Logic Look-Up Tables (LUTs). Conversely, Nikhilam implementations generally required fewer LUTs, making them more resource-efficient, but they exhibited slightly slower performance. CLA consistently delivered the best delay for both Vedic multiplier types among the adder architectures. All the explored configurations are viable for practical implementation on Xilinx ISE 14.7. The key takeaway is that the choice between Urdhva Tiryakbhyam and Nikhilam and the specific adder architecture hinges on the application’s priorities.

Nergiz Ercil Cagiltay, Sacip Toker, Kursat Cagiltay

Massive Open Online Courses (MOOCs) now offer a variety of options for everyone to obtain a high-quality education. The purpose of this study is to better understand the behaviours of MOOC learners and provide some insights for taking actions that benefit larger learner groups. Accordingly, 2,288,559 learners’ behaviours on 174 MITx courses were analysed. The results show that MOOCs are more attractive to the elderly, male, and highly educated groups of learners. Learners’ performance improves as they register for more courses and improve their skills and experiences on MOOCs. The findings suggest that, in the long run, learners’ adaptation to MOOCs will significantly improve the potential benefits of the MOOCs. Hence, MOOCs should continue by better understanding their learners and providing alternative instructional designs by considering different learner groups. MOOC providers’ decision-makers may take these findings into account when making operational decisions.

Tasya Kamila Andiani, Oscar Jayanagara

This research focuses on analyzing the influence of Workload, stress, technical skills, self-efficacy, and social competence on the performance of medical personnel in the era of the Covid-19 pandemic. This research includes quantitative descriptive analysis with a cross-sectional approach. The dependent variables in this study are the performance of medical personnel, while the independent variables are Workload, work stress, technical skills, self-efficacy, and social competence. Sample an in this study is a part of the medical personnel who provide services to a Covid-19 patient ataSukajadi Regional General Hospital, Banyuasin, South Sumatra, which totals 130 people. Take a sample using purposive sampling. Data analysis and processing using the Multiple Linear Regression method. The results showed that Workload had a negative and significant effect on the Performance of Medical Personnel at the Sukajadi Regional General Hospital, Banyuasin, South Sumatra (sig value (0.022) <Level of Significant (0.05)), Work Stress had a negative, but not significant effect on the Performance of Medical Personnel at the Sukajadi Regional General Hospital, Banyuasin, South Sumatra (sig value (0.262) > Level of Significant (0.05)), technical Skills have a positive and significant effect on the Performance of Medical Personnel at the Sukajadi Regional General Hospital, Banyuasin, South Sumatra (sig value (0.046) <Level of Significant (0.05)), Self Efficacy has a positive and significant influence on the Performance of Medical Personnel at the Sukajadi Regional General Hospital, Banyuasin, South Sumatra (sig value (0.040) <Level of Significant (0.05  )), Social Competence has a positive and significant influence on the Performance of Medical Personnel at the Sukajadi Regional General Hospital, Banyuasin, South Sumatra (sig value (0.000) <Level of Significant (0.05)),  and Workload, Work Stress, Technical Skills, Self Efficacy, and Social Competence have a joint influence on the Performance of Medical Personnel at the Sukajadi Regional General Hospital, Banyuasin, South Sumatra (sig value (0.000)     <Level of Significant (0.05)).  If Workload, Work Stress, Technical Skills, Self Efficacy, and Social Competence increase together, then the Performance of Medical Personnel at the Sukajadi Regional General Hospital, Banyuasin, South Sumatra, has increased significantly

Tongshuai Liu, Guoming Li, Zhilong Liu et al.

With the rapid development of large-scale and intensive swine production, the emission of aerosols from swine farms has become a growing concern, attracting extensive attention. While aerosols are found in various environments, those from swine farms are distinguished from human habitats, such as residential, suburban, and urban areas. In order to gain a comprehensive understanding of aerosols from swine farms, this paper reviewed relevant studies conducted between 2000 and 2022. The main components, concentrations, and size distribution of the aerosols were systematically reviewed. The differences between aerosols from swine farms and human living and working environments were compared. Finally, the sources, influencing factors, and reduction technologies for aerosols from swine farms were thoroughly elucidated. The results demonstrated that the concentrations of aerosols inside swine farms varied considerably, and most exceeded safety thresholds. However, further exploration is needed to fully understand the difference in airborne microorganism community structure and particles with small sizes (<1 μm) between swine farms and human living and working environments. More airborne bacterial and viruses were adhered to large particles in swine houses, while the proportion of airborne fungi in the respirable fraction was similar to that of human living and working environments. In addition, swine farms have a higher abundance and diversity of potential pathogens, airborne resistant microorganisms and resistant genes compared to the human living and working environments. The aerosols of swine farms mainly originated from sources such as manure, feed, swine hair and skin, secondary production, and waste treatment. According to the source analysis and factors influencing aerosols in swine farms, various technologies could be employed to mitigate aerosol emissions, and some end-of-pipe technologies need to be further improved before they are widely applied. Swine farms are advised not to increase aerosol concentration in human living and working environments, in order to decrease the impact of aerosols from swine farms on human health and restrain the spread of airborne potential pathogens. This review provides critical insights into aerosols of swine farms, offering guidance for taking appropriate measures to enhance air quality inside and surrounding swine farms.

Sergiy Plankovskyy, Yevgen Tsegelnyk, Oleksandr Pankratov et al.

Introduction. The optimization placement problem refereed to virtual localization is studied. This problem is motivated by the need to optimize the production of parts from near-net shape blanks using CNC machines. The known algorithms for solving the virtual localization problem come down to determining the location parameters of the part CAD model inside the point cloud obtained by scanning the workpiece surface. The main disadvantage of such algorithms is the use of criteria that are insensitive to the intersection of the surfaces of the part and the workpiece. In order to prevent such errors in production conditions, it is necessary to involve a human operator in conducting operations based on virtual localization. In this way, the virtual localization problem of complex shape objects is of paramount importance. The purpose of the paper is to propose a new approach for solving the virtual localization problem. Results. A new mathematical model of the virtual localization problem based on the phi-function technique is proposed. We developed a solution strategy that combines algorithm of generating feasible starting points with non-linear optimization procedure. The testing of the proposed approach was carried out for a two-dimensional case. The computational results illustrated with graphical illustrations are provided that show the efficiency of the proposed algorithm. Conclusions. The obtained results show that the use of the phi-functions technique prevents the occurrence of erroneous solutions with the intersection of the workpiece surfaces. An algorithm for solving the problem of virtual localization in a two-dimensional formulation for the case when the part and the workpiece are convex polygons has been developed. For the considered test problems, the solution time did not exceed 2.5 sec, which fully meets the requirements of industrial use. In the future, it is planned to extend the proposed method to the cases when the CAD model of the part has an arbitrary shape and is formed by Boolean operations on geometric primitives.

Andrei Popov, Myroslav Momot, Alina Yelizieva

The subject of the research are methods and technologies for automating the process of software product testing. The aim of the work is to optimize the time and costs for performing automated testing of software products. The following tasks were solved: analysis of existing software testing automation systems; formation of system of selection criteria for testing automation systems; development of formalized model of selection process; development of automation system selection algorithm considering customer's requirements; development of UML diagrams for presentation of functional capabilities of developed application; development of application for informational support of selection process. To solve these tasks, we used methods of system analysis, theory of sets and technologies of cross-platform applications development. The following results were obtained: The most popular systems of test automation have been analyzed, their scope and main capabilities have been singled out. Selection criteria are singled out, divided into qualitative and quantitative. Formalized model for choosing test automation systems taking into account their characteristics and customer requirements is proposed. Developed UML diagram shows the functionality of the developed subsystem. The proposed algorithm for determining the re-recommended system of test automation allows us to take into account the vectors of criteria for testing systems. On the basis of the formalized model and algorithm we developed a subsystem that allows us to determine the optimal variant of test automation system on the basis of the introduced selection criteria. Conclusions: informational support for choosing a test automation system for software products based on the developed algorithm takes into account the customer's requirements and the characteristics of the existing systems, which allows us to select the most preferable option out of the possible systems. The main result of the developed subsystem is a recommendation for a user to use an automated testing system, taking into account customer requirements.

Pinasti Dwi Utami, Hilda Putri Mauludiyah, Bramesvia Ravinka et al.

Meeting food needs is one of the main problems for a country. Cultivation of horticultural crops with verticulture techniques is one form of activity that can be a way to meet food needs. The crop yield can be used for personal consumption and sold as a source of additional income for households. The verticulture is made from waste which are used as containers or pots and then planted with chili and mustard plants. This activity aims to improve skills, creativity, meet food needs and use empty land that can add aesthetic value. Participants consisted of 27 heads of neighborhood, the women's association for family welfare development (Pembinaan Kesejahteraan Keluarga, PKK) and Youth Organizations in Jati Village, Sumberlawang District, Sragen Regency, Sragen, with 46 participants of various ages. The activity was guided and carried out by the UNS 65 KKN team with enthusiasm and enthusiastically welcomed by the participants. The evaluation was carried out by interviewing several participants. The response showed that the activity was carried out well and the knowledge conveyed was also well received. Based on the results of these interviews, it can be seen that around 85% of participants can understand the socialization and practice of verticulture cultivation well.

Xiao Xue, Guanding Li, Deyu Zhou et al.

With the mutual interaction and dependence of several intelligent services, a crowd intelligence service network has been formed, and a service ecosystem has gradually emerged. Such a development produces an ever-increasing effect on our lives and the functioning of the whole society. These facts call for research on these phenomena with a new theory or perspective, including what a smart society looks like, how it functions and evolves, and where its boundaries and challenges are. However, the research on service ecosystems is distributed in many disciplines and fields, including computer science, artificial intelligence, complex theory, social network, biological ecosystem, and network economics, and there is still no unified research framework. The researchers always have a restricted view of the research process. Under this context, this paper summarizes the research status and future developments of service ecosystems, including their conceptual origin, evolutionary logic, research topic and scale, challenges, and opportunities. We hope to provide a roadmap for the research in this field and promote sound development.

Xiaojian Yi, Zhezhe Wang, Shulin Liu et al.

Durability evaluation plays an important role in product operation and maintenance during the design stage. In order to ensure a long life, high reliability, and short development cycle, an accelerated degradation durability evaluation model for the turbine impeller of a turbine based on a genetic algorithms back-propagation neural network is established. Based on the proposed model, we discuss two types of practical problems. One is the matching problem of the component strengthening test and whole machine system test. The other is the design problem of two kinds of bench tests. All in all, this work not only proposes a durability evaluation model to effectively solve the current turbine durability evaluation problems, but it also provides a feasible research idea for similar problems.