Hasil untuk "Regulation of industry, trade, and commerce. Occupational law"

Sameh Affi, Imed Miraoui, Atef Khedher

In modern Industry 4.0 environments, real-time scheduling presents a complex challenge requiring both formal correctness guarantees and optimal performance. <i>Background</i>: Traditional approaches fail to provide an optimal integration between formal correctness guaranteeing and optimization, and such failure either produces suboptimal results or a correct result lacking guarantee, and studies have indicated that poor scheduling decisions could cause productivity losses of up to 20–30% and increased operational costs of up to USD 2.5 million each year in medium-scale manufacturing facilities. <i>Methods</i>: This work proposes a new hybrid approach by integrating Extended Time Petri Nets (ETPNs) and Finite-State Automata (FSAs) with formal modeling, abstracting ETPNs by extending conventional Time Petri Nets to deterministic time and priority systems, accompanied by Genetic Algorithms (GAs) to optimize the solution to tackle a multi-objective optimization problem. Our solution tackles indeterministic problems by incorporating suitable priority resolution methods and GA to pursue optimal solutions to very complex scheduling problems and starting accurately from standard real-time scheduling-policy models such as DM, RM, and EDF-EDF. <i>Results</i>: Experimental evaluation has clearly verified performance gains up to 48% above conventional techniques, covering completely synthetic and practical case studies, including 31–48% improvement on synthetic benchmarks, 24% increase on resource allocation, and total elimination of constraint violations. <i>Conclusions</i>: The new proposed hybrid technique is, to a considerable extent, a dramatic advancement within real-time scheduling techniques and Industry 4.0, successfully and effectively integrating optimal correctness guaranteeing and favorable GA-aided optimization techniques, which particularly guarantee optimal correctness to safe-related applications and provide considerable improvements to support efficient and optimal performance, extremely helpful within Industry 4.0.

Yuxin Qin, Ke Cao, Haowei Liu et al.

E-commerce product poster generation aims to automatically synthesize a single image that effectively conveys product information by presenting a subject, text, and a designed style. Recent diffusion models with fine-grained and efficient controllability have advanced product poster synthesis, yet they typically rely on multi-stage pipelines, and simultaneous control over subject, text, and style remains underexplored. Such naive multi-stage pipelines also show three issues: poor subject fidelity, inaccurate text, and inconsistent style. To address these issues, we propose InnoAds-Composer, a single-stage framework that enables efficient tri-conditional control tokens over subject, glyph, and style. To alleviate the quadratic overhead introduced by naive tri-conditional token concatenation, we perform importance analysis over layers and timesteps and route each condition only to the most responsive positions, thereby shortening the active token sequence. Besides, to improve the accuracy of Chinese text rendering, we design a Text Feature Enhancement Module (TFEM) that integrates features from both glyph images and glyph crops. To support training and evaluation, we also construct a high-quality e-commerce product poster dataset and benchmark, which is the first dataset that jointly contains subject, text, and style conditions. Extensive experiments demonstrate that InnoAds-Composer significantly outperforms existing product poster methods without obviously increasing inference latency.

Supanida Nanthawong, Panuwat Wisutwattanasak, Chinnakrit Banyong et al.

<i>Background</i>: Truck drivers are a vital workforce sustaining Thailand’s freight transport, particularly in Northeastern Thailand (Isan), a major logistics hub connecting with Laos, Vietnam, and Cambodia via Highway No. 2 and the AEC network. However, these drivers face disproportionately high risks of severe road accidents due to occupational factors such as fatigue, time pressure, and long-distance driving. <i>Methods</i>: This study developed and validated a second-order confirmatory factor analysis (CFA) model to examine the multidimensional structure of risky driving behavior among Thai truck drivers. Grounded in the Driver Behavior Questionnaire (DBQ), the framework was extended to include seven dimensions: traffic violations, errors, lapses, aggressive behavior, substance use, technology-related distractions, and pedestrian-related risks. <i>Results</i>: Data were collected from 400 truck drivers in Isan using a structured questionnaire. CFA results confirmed the model’s structural validity, with satisfactory fit indices (X²/df = 2.122, CFI = 0.913, TLI = 0.897, RMSEA = 0.053, SRMR = 0.079). <i>Conclusions</i>: The findings reveal that risky driving behavior in this group extends beyond traditional DBQ categories, incorporating emerging risks specific to the commercial transport environment. This framework can be effectively utilized for risk assessment, behavioral screening, and the development of targeted safety interventions for this high-risk occupational group.

Mansour Fakhri, Yousef Rahimizadeh, Morteza Esmaeili

The use of tire-derived aggregates (TDA) in railway infrastructure has gained significant attention in recent years due to its potential benefits, including vibration mitigation, ballast degradation reduction, increased damping, decreased stiffness, and improved dynamic performance of bridges. However, one major concern regarding the use of TDA-ballast mixes is the potential for increased settlement, primarily due to the softer nature of rubber particles. Hence, investigating the effect of TDA content and size on track settlement and identifying the optimal mix configuration is of critical importance. This study evaluates these effects through a series of laboratory ballast box tests conducted on different mixtures. The experimental program included pure ballast samples (as control) and ballast-TDA mixes with 5%, 10%, 15%, and 20% TDA by weight. Two TDA size ranges were considered: fine particles (10–20 mm diameter) and coarse particles (comparable to ballast size). The results revealed that, except for the mix with 10% coarse TDA—which exhibited a 1.7% reduction in settlement compared to the control—all other mixes (with 5%, 15%, and 20% coarse TDA) experienced increased settlement by 24%, 155%, and 217%, respectively. Furthermore, settlement increased significantly with rising TDA content in mixes using fine particles. Specifically, the increases in settlement for 5%, 10%, 15%, and 20% fine TDA mixes, compared to the pure ballast sample, were 22%, 88%, 234%, and 310%, respectively. Based on the results, the mix with 10% coarse TDA is recommended as the optimal configuration, offering improved long-term performance without compromising stability. These findings provide valuable insight for the design and optimization of ballast–TDA mixes, facilitating the effective integration of recycled materials in railway tracks while mitigating long-term settlement issues.

Juan Gabriel França Canon, Robério José Rogério dos Santos, Victor Diogho Heuer de Carvalho et al.

<i>Background</i>: Logistics and supply chain management are crucial in modern commerce, impacting global competition, and both can directly benefit by using enterprise resource planning (ERP) systems. This case study examines key success factors behind a significant operational transformation in a company in the countryside of Alagoas, Brazil. From this context, two research questions emerge: (a) What are the main success factors that drove a significant operational transformation in logistics and supply chain management, and how did these factors impact the company’s growth? (b) How does digital transformation and adopting an ERP impact the company’s logistics activities? <i>Methods</i>: Data were collected through on-site observations, interviews with supervisors and a manager, and analysis of company-provided documentation. <i>Results</i>: The study identified key processes, stakeholders, and practices, focusing on critical success factors, mission-critical processes, and the integration of core and support functions. Notable changes were observed through key logistics performance indicators, tracking the evolution from pre-implementation to post-implementation and revealing their impact on the company’s growth. <i>Conclusions</i>: Improved decision making between departments significantly enhanced performance and growth. The analyzed company’s success can be attributed to a process-oriented approach, digital transformation in logistics, and investment in information technology.

Gaetan de Rassenfosse

Intellectual property (IP) rules have the potential to shape cross-border trade far more than their legalistic origins might suggest. Drawing on three decades of evidence, this review shows that stronger IP rights simultaneously create market-power forces that raise prices and market-expansion forces that broaden demand, while dynamic incentives spur quality upgrading and new export varieties. Micro-data and quasi-natural experiments after TRIPS reveal that IP most often boosts trade along the extensive margin and redirects some activity toward licensing and foreign investment. Policy bundling and measurement gaps on the strength of IP rights still cloud causal inference. Future work must map intangible flows and enforcement quality to capture the digital, data-driven frontier of international commerce.

Mohammad Anwar Rahman, E. Daniel Kirby

This study investigates the transformation of e-commerce warehouse operations by integrating Lean Six Sigma tools to enhance efficiency and sustainability. Beginning with Value Stream Mapping (VSM) to identify inefficiencies, followed by a Hoshin Kanri plan to align improvement initiatives with strategic objectives, the study implemented measures such as pallet pooling, process standardization, automation in inspection and picking, layout optimization, and Kanban systems for continuous improvement. A case study of a local e-commerce warehouse specializing in medical devices and healthcare products identified 29 activities across receiving, inspection, storing, picking, packing, and shipping, highlighting inefficiencies addressed through Lean-driven initiatives. These efforts resulted in a 23% reduction in total lead time, doubled value-added time, and significant improvements in inspection, picking, packing, and automation, reducing delays, lowering costs, and enhancing workflow. The study fills a gap in the literature by integrating multiple Lean tools and utilizing the Critical to Quality (CTQ) matrix to ensure sustainable improvements in e-commerce warehousing, emphasizing the strategic value of Lean Six Sigma in creating efficient, customer-focused operations.

Katarzyna Biskup-Grabowska

Ciągły rozwój lotnictwa cywilnego, a co za tym idzie – infrastruktury lotniczej, stawia przed ustawodawcą wyzwania związane z potrzebą zminimalizowania negatywnego wpływu działalności lotniczej na środowisko naturalne. W artykule wskazano, że istnieje wiele regulacji, które zapewniają ochronę środowiska przed skutkami działalności lotniczej. Ponadto zwrócono uwagę na dynamikę liczby operacji lotniczych na terytorium Rzeczypospolitej Polskiej zgodnie z prognozami do 2040 r. W konsekwencji podkreślono, iż działania organów międzynarodowych, europejskich oraz ustawodawcy krajowego powinny się skupiać na zwiększaniu obostrzeń dotyczących ochrony środowiska w związku z rozwojem działalności lotniczej.

Dennis Junger, Max Westing, Christopher P. Freitag et al.

Progressing digitalization and increasing demand and use of software cause rises in energy- and resource consumption from information and communication technologies (ICT). This raises the issue of sustainability in ICT, which increasingly includes the sustainability of the software products themselves and the art of creating sustainable software. To this end, we conducted an analysis to gather and present existing literature on three research questions relating to the production of ecologically sustainable software ("Green Coding") and to provide orientation for stakeholders approaching the subject. We compile the approaches to Green Coding and Green Software Engineering (GSE) that have been published since 2010. Furthermore, we considered ways to integrate the findings into existing industrial processes and higher education curricula to influence future development in an environmentally friendly way.

Joaquín Arias, Mar Moreno-Rebato, José A. Rodríguez-García et al.

Automated legal reasoning and its application in smart contracts and automated decisions are increasingly attracting interest. In this context, ethical and legal concerns make it necessary for automated reasoners to justify in human-understandable terms the advice given. Logic Programming, specially Answer Set Programming, has a rich semantics and has been used to very concisely express complex knowledge. However, modelling discretionality to act and other vague concepts such as ambiguity cannot be expressed in top-down execution models based on Prolog, and in bottom-up execution models based on ASP the justifications are incomplete and/or not scalable. We propose to use s(CASP), a top-down execution model for predicate ASP, to model vague concepts following a set of patterns. We have implemented a framework, called s(LAW), to model, reason, and justify the applicable legislation and validate it by translating (and benchmarking) a representative use case, the criteria for the admission of students in the "Comunidad de Madrid".

Naseela Pervez, Alexander J. Titus

Biotechnology Industry 5.0 is advancing with the integration of cutting-edge technologies like Machine Learning (ML), the Internet Of Things (IoT), and cloud computing. It is no surprise that an industry that utilizes data from customers and can alter their lives is a target of a variety of attacks. This chapter provides a perspective of how Machine Learning Security Operations (MLSecOps) can help secure the biotechnology Industry 5.0. The chapter provides an analysis of the threats in the biotechnology Industry 5.0 and how ML algorithms can help secure with industry best practices. This chapter explores the scope of MLSecOps in the biotechnology Industry 5.0, highlighting how crucial it is to comply with current regulatory frameworks. With biotechnology Industry 5.0 developing innovative solutions in healthcare, supply chain management, biomanufacturing, pharmaceuticals sectors, and more, the chapter also discusses the MLSecOps best practices that industry and enterprises should follow while also considering ethical responsibilities. Overall, the chapter provides a discussion of how to integrate MLSecOps into the design, deployment, and regulation of the processes in biotechnology Industry 5.0.

Pau Pujolas, Jack Rossbach

Trade imbalances significantly alter the welfare implications of tariffs. Using an illustrative model, we show that trade deficits enhance a country's ability to alter its terms of trade, and thereby benefit from tariffs. Greater trade deficits imply higher optimal, or welfare maximizing, tariffs. We compute optimal unilateral and Nash equilibrium tariffs between the United States and China $\unicode{x2014}$ the countries with the largest bilateral trade imbalance $\unicode{x2014}$ using a multi-region, multi-sector applied general equilibrium model with service sectors and input-output linkages, a computationally complex task. Free trade benefits both countries compared to a trade war. Relative to existing tariff rates, however, the United States gains from a trade war with China $\unicode{x2014}$ a result that hinges on their bilateral trade imbalance.

Chester Palen-Michel, Ruixiang Wang, Yipeng Zhang et al.

The emergence of Large Language Models (LLMs) has revolutionized natural language processing in various applications especially in e-commerce. One crucial step before the application of such LLMs in these fields is to understand and compare the performance in different use cases in such tasks. This paper explored the efficacy of LLMs in the e-commerce domain, focusing on instruction-tuning an open source LLM model with public e-commerce datasets of varying sizes and comparing the performance with the conventional models prevalent in industrial applications. We conducted a comprehensive comparison between LLMs and traditional pre-trained language models across specific tasks intrinsic to the e-commerce domain, namely classification, generation, summarization, and named entity recognition (NER). Furthermore, we examined the effectiveness of the current niche industrial application of very large LLM, using in-context learning, in e-commerce specific tasks. Our findings indicate that few-shot inference with very large LLMs often does not outperform fine-tuning smaller pre-trained models, underscoring the importance of task-specific model optimization.Additionally, we investigated different training methodologies such as single-task training, mixed-task training, and LoRA merging both within domain/tasks and between different tasks. Through rigorous experimentation and analysis, this paper offers valuable insights into the potential effectiveness of LLMs to advance natural language processing capabilities within the e-commerce industry.

Elmenshawy Adham Ahmed Awad Elsayed, Alomar Iyad, Arshad Ali

The aim of this paper is to optimize turbine blade cooling channels by applying jet impingement Method. The selection of experiment data for NASA 3CX turbine blade, and 3D model using solidworks software and create computational fluid dynamics (CFD) simulations used to model the coolant flow and temperature distribution in the vane, while experimental testing can validate the CFD results and provide additional insights into the cooling system's performance., ANSYS FLUENT code was used as a CFD solver, and ANSYS ICEM-CFD was used for mesh generation. MATLAB code is used for calculation using experiment data and this was helpful for simulations. Heat transfer conjugation analysis bases SST shear stress analyses K-ω turbulent model. The results conclude that providing additional information about the cooling channels and how they differ in the studies being compared. The results demonstrate that the cooling channels' hydraulic diameter decreases by a significant percentage (up to 49.70%–69.55%) as they are drawn to the trailing edge of the blade. This can have a significant impact on the heat transfer coefficients and the performance of the cooling system. The pressure side of the turbine blade is observed to follow the Hylton Model, while the current study predicts a large over-anticipated heat transfer coefficient around the Turbine blade head and on the bulk of the suction side. In terms of average heat transfer coefficient, the two models differ by 23.36%. The authors found that the cooling effectiveness for the Optimized jet impingement model is 0.4892 for whole blade and compared it with the cooling effectiveness for the optimized jet impingement model, which is 0.6936, The results of the comparison between the base model and the optimized jet impingement model suggest that the optimized model has a significantly higher cooling effectiveness. The increase in cooling effectiveness of 29.46% for the whole blade and 28.823% for the trailing edge indicates that the optimized jet impingement design provides improved cooling performance. These results highlight the importance of considering optimized cooling designs for turbine blades to maintain efficient and safe operation.

Ricardo Moreira da Silva, Guilherme Francisco Frederico, Jose Arturo Garza-Reyes

<i>Background:</i> Industry 4.0 is one of the topics related to manufacturing, supply chain and logistics that has received great interest from the academic community, organizations and governments in the last decade. <i>Problem statement:</i> Several published articles discuss and seek to conceptualize what the fourth industrial revolution is, but no research relates Industry 4.0 in the context of logistics service providers (LSPs) in a clear and structured way. <i>Objectives:</i> This study aims to fill this research gap, proposing a conceptual framework and addressing the challenges, barriers and organizational dimensions that need adaptation to insert LSPs in the new Industry 4.0 environment. <i>Methods:</i> This theoretical and conceptual study uses the Systematic Literature Review (SLR) as a research method to understand the Industry 4.0 phenomenon in the context of LSPs. <i>Contributions:</i> The relevant constructs identified in this research will help professionals and organizations that provide logistics services to develop strategies and encourage new research in the field of Industry 4.0 from the perspective of LSPs. <i>Results:</i> In addition, this research identified and generally consolidated six dimensions, as a result of this innovative study a conceptual framework is presented.

Robert Lee Poe

Employment selection processes that use automated hiring systems based on machine learning are becoming increasingly commonplace. Meanwhile, concerns about algorithmic direct and indirect discrimination that result from such systems are front-and-center, and the technical solutions provided by the research community often systematically deviate from the principle of equal treatment to combat disparate or adverse impacts on groups based on protected attributes. Those technical solutions are now being used in commercially available automated hiring systems, potentially engaging in real-world discrimination. Algorithmic fairness and algorithmic non-discrimination are not the same. This article examines a conflict between the two: whether such hiring systems are compliant with EU non-discrimination law.

Milivoje M. Kostic

This comprehensive treatise is written for the special occasion of the author's 70th birthday. It presents his lifelong endeavors and reflections with original reasoning and re-interpretations of the most critical and misleading issues in thermodynamics; since now, we have the advantage to look at the historical developments more comprehensively and objectively than the pioneers. Starting from Carnot (grandfather of thermodynamics-to-be) to Kelvin and Clausius (fathers of thermodynamics), and other followers, the most relevant issues are critically examined and put in historical and contemporary perspective. From original reasoning of energy forcing and displacement to logical proofs of the fundamental laws, to ubiquity of thermal motion and heat, and indestructibility of entropy, including the new concept of "thermal roughness" and the inevitability of dissipative irreversibility, to "dissecting Carnot true reversible-equivalency" and critical concept of "Carnot-Clausius heat-work equivalency (CCHWE)" regarding the interchangeability of heat and work, and to demonstrating "no hope" for the "challengers" of the Second Law of thermodynamics, among others, are offered. It is hoped that the novel contributions presented will enhance comprehension and resolve some of the fundamental issues, as well as promote collaboration and future progress.

Büşra Ayan, Elif Güner, Semen Son-Turan

<i>Background</i>: This study presents a comprehensive review of blockchain technology with a sustainability orientation in supply chains and logistics. <i>Methods</i>: The publications are extracted from the Scopus and Web of Science databases, comprising 552 publications between 2017 and 2022. Several bibliometric laws and techniques, namely three-field analysis, Bradford’s Law, Lotka’s Law, and thematic maps, are applied in R with the bibliometrix package. Content analysis is also carried out based on 185 publications to appreciate the industry-based view of the field. <i>Results</i>: The bibliometric results indicate that this field is on the rise. Authors, sources, affiliations, countries, keywords, and their relationships are also addressed. The findings of the content analysis and thematic maps reveal that some of the most highlighted themes in the literature include traceability, COVID-19, the internet of things, and Industry 4.0. The most popular industry in this field is discovered to be food and agriculture. <i>Conclusions</i>: This paper contributes to the still relatively scarce literature on how blockchain technology fosters sustainable supply chains and logistics, providing a closer look at blockchain use, methodologies, and future directions for different industries concerning food, agriculture, fashion, textile and apparel, manufacturing, automotive, maritime and shipping, healthcare and pharmaceutical, mining and mineral, and energy.

Redakcja PPGiOŚ

Abualhaj Mosleh M., Abu-Shareha Ahmad A., Shambour Qusai Y. et al.

Old telecommunication systems are gradually being replaced by a new system that works over IP networks, which is known as voice over internet protocol (VoIP). VoIP has several merits (e.g., very cheap call rate), which make it increasingly popular in the telecommunication world. However, VoIP faces numerous impediments that decelerate its promotion. One of the top impediments is the wasted bandwidth caused by VoIP systems. Numerous methods have been proposed to handle this impediment, including packet aggregation methods. This paper proposes a novel aggregation method, called packet aggregation and carrier header (PA-CH), to reduce the amount of the large bandwidth caused by VoIP. As the name suggests, PA-CH saves in bandwidth by aggregating the packets in a header and using the redundant fields in the packet header to carry a portion of the packet voice data. The performance of the introduced PA-CH method was investigated based on three main metrics, namely, link capacity, allocated bandwidth reduction, and voice data shortening. Simulation results indicate that the proposed PA-CH method outperforms the comparison methods in three factors. For instance, the proposed method’s allocated bandwidth reduction ratio reaches 51% when the number of calls running concurrently reaches 100. Therefore, the proposed PA-CH method achieves its goal of reducing the wasted bandwidth caused by VoIP.