Background: Waste collectors face multi-faceted health risks including exposure to musculoskeletal disorders, respiratory diseases, and workplace injuries because of their hazardous work environment. The purpose of th...
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Background: Waste collectors face multi-faceted health risks including exposure to musculoskeletal disorders, respiratory diseases, and workplace injuries because of their hazardous work environment. The purpose of this study was to determine the risk factors that affect health of the waste collectors across Bangladesh. Methods: Data on a cross-sectional survey obtained information from 481 waste collectors about their demographics, housing conditions, hygiene practices, security measures, and disease prevalence. Descriptive analyses and multi-level models are used. Results: As per univariate analysis, 81.3% did not have access to clean water, 58.4% did not have access to sanitation, and 65.9% of people lived in unhealthy housing. According to bivariate analysis, there is an association between unhealthy working conditions i.e., respiratory illnesses (19.1% asthma, 29.7% cough), gastrointestinal issues (59.3% discomfort, 24.1% diarrhea), musculoskeletal disorders, and dermatological diseases, and unsafe working conditions (i.e., 60% no masks, 71% no gloves, and 75% no boots). Considering geographic clustering, multi-level modeling examined how different factors affected particular illnesses. The following were significant protective factors: better housing (80% lower odds of acute irritation), security measures (50% lower odds of gastrointestinal diseases), good hygiene (62% lower odds of dermatological diseases), and younger age (2% higher odds of respiratory diseases per year). Conclusion: In summary, unsafe living and working conditions greatly push the risks of illness for waste collectors. These risks to occupational health can be reduced with targeted interventions that enhance housing, hygiene, security protocols, and working conditions. (c) 2024 Occupational Safety and Health Research Institute. Published by Elsevier B.V. on behalf of Institute, Occupational Safety and Health Research Institute, Korea Occupational Safety and Health Agency. This is an open ac
multi-level modeling is a modeling paradigm that has been becoming more and more popular in recent years. The ultimate goal of multi-level modeling is to reduce accidental complexity that may arise from modeling metho...
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ISBN:
(纸本)9789897584008
multi-level modeling is a modeling paradigm that has been becoming more and more popular in recent years. The ultimate goal of multi-level modeling is to reduce accidental complexity that may arise from modeling methodologies that are not suitable to describe multi-level models. However, currently, most multi-level modeling approaches are dependent on classical modeling facilities, like OMG's four-levelmodeling architecture. The potency notion is one of the most widely-used enablers of multi-level modeling that governs the depth model elements can be instantiated at. In this paper, we propose an alternative implementation to the first incarnation of the potency notion, the so-called classic potency notion. Its multi-level nature is mapped into our multi-layer modeling framework, which liberates it from direct dependence on classical modeling facilities. We examine the proposed mapping in details and also demonstrate it via a simple case study. This work is aimed as the first step towards a generic multi-level modeling framework where researchers can freely experiment with novel multi-level modeling ideas and can share and compare their results without worrying about any sorts of tool dependence.
A multi-level approach to modeling power factor correction (PFC) rectifier and de-dc converter modules in interconnected switching power supply systems is illustrated in this paper. A three-level hierarchy for modelin...
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ISBN:
(纸本)9781424407132
A multi-level approach to modeling power factor correction (PFC) rectifier and de-dc converter modules in interconnected switching power supply systems is illustrated in this paper. A three-level hierarchy for modeling these modules is proposed and defined. The most recent results from simulations and experiments are provided to show effectiveness of the proposed approach.
This paper presents a contribution to the multi 2023 Warehouse Challenge issued to assess the capabilities and limits of multi-level modeling approaches and to foster discussion in the community. The challenge specifi...
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ISBN:
(纸本)9798400706226
This paper presents a contribution to the multi 2023 Warehouse Challenge issued to assess the capabilities and limits of multi-level modeling approaches and to foster discussion in the community. The challenge specifies a warehouse that contains product specifications and product copies that can have different features at different abstraction levels. The solution was developed using the Dynamic multi-Layer Algebra (DMLA), a multi-layer modeling approach. First, we briefly introduce DMLA and the background of the challenge. Then, we discuss our interpretation of the challenge requirements, present our model and analyze how it fulfills the requirements of the challenge. Finally, we discuss the merits and limitations of the solution and the mandatory discussion aspects of the challenge.
Model-driven engineering of software intensive systems requires adequate means for describing their essential properties. For the domain of testbed automation systems, conventional modeling formalisms fall short due t...
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ISBN:
(纸本)9780769537849
Model-driven engineering of software intensive systems requires adequate means for describing their essential properties. For the domain of testbed automation systems, conventional modeling formalisms fall short due to the inadequacy of a fixed meta-level hierarchy. In this paper we identify the core problems by examining real-world examples. As a solution, we propose using a unification of classes and objects, known as clabjects. We propose extensions to the basic clabject notion for handling connector inheritance and instantiation, which are essential for bridging the gap between theoretical foundations and industrial applications.
At present, manufacturing processes are highly tailored to a specific product. Changes in product requirements therefore lead to big manual efforts for adapting the manufacturing process and reconfiguring production r...
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ISBN:
(纸本)9781450366281
At present, manufacturing processes are highly tailored to a specific product. Changes in product requirements therefore lead to big manual efforts for adapting the manufacturing process and reconfiguring production resources accordingly. Existing approaches do not cope well with this complexity. This hinders agile, customer-oriented manufacturing. A promising approach for automated assembling processes is the Machine as a Service paradigm, which aims for providing production resources on demand. This requires a consistent and pervasive formalization of product specifications, the corresponding manufacturing resources and their interdependencies. Thus, our first contribution is a generic and extensible multi-level and modular modeling framework to formalize products and available resources. Our framework is scalable for large companies and enables reuse for cross-company collaboration and supplier integration. Thereby, the static relationship between product, process and resource is avoided by describing product features and resource skills in separate models. Our framework uses the standardized SysML/UML. Our second contribution is the ability of our framework to integrate different standards. For demonstration, we apply our multi-level approach to a flexible assembly of terminal boxes for transmission gears and show the integration of standards by embedding the eCl@ss classification.
Conceptual modeling promises to support various analysis questions on organizational structures, such as allocation of tasks, responsibilities, and authority in an organization. In this paper, we first synthesize requ...
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Conceptual modeling promises to support various analysis questions on organizational structures, such as allocation of tasks, responsibilities, and authority in an organization. In this paper, we first synthesize requirements on an organizational structure analysis from the business scholar literature and assess to what extent and how current modeling languages fulfill these. In particular, we find limitations in the covered scope as well as the information processing capabilities of the reviewed approaches. Second, as a response to identified gaps, we propose multi-level modeling and integrated modeling and programming as a way to support design and analysis of organizational structure. We use the structure of universities as a case scenario. This paper is an extension of our earlier work. Firstly, we add an explicit set of requirements derived from business scholar literature. Secondly, we draw a comparison to the abstraction mechanisms used in conventional meta-modeling, as prominently exemplified by UML class diagrams, and we critically discuss multi-level modeling. Finally, we discuss a prototypical implementation of our multi-level model in the XModeler software tool.
The growth of multi-level modeling has resulted in an increase of level-organization alternatives which significantly differ from each other with respect to their underlying foundations and the well-formedness rules t...
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The growth of multi-level modeling has resulted in an increase of level-organization alternatives which significantly differ from each other with respect to their underlying foundations and the well-formedness rules they enforce. Alternatives substantially diverge with respect to how level boundaries should govern instance-of relationships, what modeling mechanisms they employ, and what modeling principles they establish. In this article, I analyze how a number of multi-level modeling approaches deal with certain advanced modeling scenarios. In particular, I identify linear domain metamodeling, i.e., the requirement that all domain-induced instance-of relationships align with a single global level-hierarchy, as a source of accidental complexity. I propose a novel multi-dimensional multi-level modeling approach based on the notion of orthogonal ontological classification that supports modeling of domain scenarios with minimal complexity while supporting separation of concerns and sanity-checking to avoid inconsistent modeling choices.
multi-level modeling is currently regaining attention in the database and software engineering community with different emerging proposals and implementations. One driver behind this trend is the need to reduce model ...
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multi-level modeling is currently regaining attention in the database and software engineering community with different emerging proposals and implementations. One driver behind this trend is the need to reduce model complexity, a crucial aspect in a time of analytics in Big Data that deal with complex heterogeneous data structures. So far no standard exists for multi-level modeling. Therefore, different formalization approaches have been proposed to address multi-level modeling and verification in different frameworks and tools. In this article, we present an approach that integrates the formalization, implementation, querying, and verification of multi-level models. The approach has been evaluated in an open-source F-Logic implementation and applied in a large-scale data interoperability project in the oil and gas industry. The outcomes show that the framework is adaptable to industry standards, reduces the complexity of specifications, and supports the verification of standards from a software engineering point of view.
Wireless network technology keeps improving by solving problems detected in current systems and anticipating requirements for future systems. One of the possible approaches to help advancing wireless technology is to ...
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Wireless network technology keeps improving by solving problems detected in current systems and anticipating requirements for future systems. One of the possible approaches to help advancing wireless technology is to develop methods that help researchers understand the less desired behaviors that may occur in a real-world system. One such method is data driven multi-level analysis that uses the monitoring data collected from real-world networks to provide detailed insight, at several levels and/or scales, into the system behavior. This paper discusses data driven multi-level analysis, provides a proof of concept on how it can be applied and identifies challenges. The contributions of this paper are (1) the use of data driven multi-level analysis for understanding the behaviour of wireless networks and (2) the identification of open challenges and directions for future research.
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