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نتیجه جستجو - SEM

تعداد مقالات یافته شده: 1333
ردیف عنوان نوع
41 Keywords: Antimicrobial resistance Stakeholder mapping Veterinary drugs Policy regulation Supply chain Public and private sector collaboration National action plan
درک زنجیره تأمین آنتی بیوتیک های دامپزشکی برای رفع مقاومت ضد میکروبی در PDR لائوس: نقش ها و تعاملات سهامداران درگیر-2021
In response to the global call to mitigate risks associated with antimicrobial resistance (AMR), new regulations on the access and use of veterinary antibiotics are currently being developed by the Lao government. This study aims to explore how the implementation of these new regulations might effectively reduce and adapt the sale, distribution and use of veterinary antibiotics in Lao PDR. To this end, we used the theory of change, framing the AMR issue within the context of the stakeholders involved in the veterinary antibiotics supply chain. Qualitative and quantitative methods were used to collect data, based on questionnaires (n=36 antibiotic suppliers, n=96 chicken farmers, n=96 pig farmers), and participatory tools such as a workshop (n=10 participants), semi-structured interviews (n=20), and focus group discussions (n=7 participants). The stakeholders understanding of the AMR issue and potential challenges related to the implementation of new regulations regarding access and use of antibiotics, were also investigated. We mapped the veterinary antibiotic supply chain in Lao PDR, and analysed the roles and interactions of its stakeholders. Twenty-three stakeholders representing the private and the public sectors were identified. Many informal and formal links connected these stakeholder within this supply chain. The lack of veterinarian-farmer interaction and the evolving nature of the veterinary antibiotics supply chain accentuated the challenges of achieving behaviour change through regulations. Most of the antibiotics found on farms were categorized by the World Health Organizations as critically important antibiotics used in human medicine. We argue that AMR risk mitigation strategy requires dialogue and engagement between private and publicsectors stakeholders, involved in the importation, distribution, sale and use of veterinary antibiotics. This study further highlighted that AMR is a complex adaptive challenge requiring multi-sectoral approach. We believed that a sustainable approach to reduce and adapt veterinary antibiotics use should be prepared in collaboration with stakeholders from private and public sectors identified in this study, in addition to the new regulations. This collaboration should start with the co-construction of a common understanding of AMR issue and of the objectives of new regulations.
Keywords: Antimicrobial resistance | Stakeholder mapping | Veterinary drugs | Policy regulation | Supply chain | Public and private sector collaboration | National action plan
مقاله انگلیسی
42 Combining computer vision with semantic reasoning for on-site safety management in construction
ترکیب بینایی ماشین با استدلال معنایی برای مدیریت ایمنی در هر دو سو در ساخت -2021
Computer vision has been utilized to extract safety-related information from images with the advancement of video monitoring systems and deep learning algorithms. However, construction safety management is a knowledge-intensive task; for instance, safety managers rely on safety regulations and their prior knowledge during a jobsite safety inspection. This paper presents a conceptual framework that combines computer vision and ontology techniques to facilitate the management of safety by semantically reasoning hazards and corre- sponding mitigations. Specifically, computer vision is used to detect visual information from on-site photos while the safety regulatory knowledge is formally represented by ontology and semantic web rule language (SWRL) rules. Hazards and corresponding mitigations can be inferred by comparing extracted visual information from construction images with pre-defined SWRL rules. Finally, the example of falls from height is selected to validate the theoretical and technical feasibility of the developed conceptual framework. Results show that the proposed framework operates similar to the thinking model of safety managers and can facilitate on-site hazard identi- fication and prevention by semantically reasoning hazards from images and listing corresponding mitigations. 1. Introduction
keywords: بینایی ماشین | هستی شناسی | استدلال معنایی | شناسایی ریسک | مدیریت ایمنی ساخت | Computer vision | Ontology | Semantic reasoning | Hazard identification | Construction safety management
مقاله انگلیسی
43 The effect of WeChat-based training on improving the knowledge of tuberculosis management of rural doctors
تأثیر آموزش مبتنی بر وی چت بر ارتقای دانش مدیریت سل در پزشکان روستایی-2021
Computer vision has been utilized to extract safety-related information from images with the advancement of video monitoring systems and deep learning algorithms. However, construction safety management is a knowledge-intensive task; for instance, safety managers rely on safety regulations and their prior knowledge during a jobsite safety inspection. This paper presents a conceptual framework that combines computer vision and ontology techniques to facilitate the management of safety by semantically reasoning hazards and corresponding mitigations. Specifically, computer vision is used to detect visual information from on-site photos while the safety regulatory knowledge is formally represented by ontology and semantic web rule language (SWRL) rules. Hazards and corresponding mitigations can be inferred by comparing extracted visual information from construction images with pre-defined SWRL rules. Finally, the example of falls from height is selected to validate the theoretical and technical feasibility of the developed conceptual framework. Results show that the proposed framework operates similar to the thinking model of safety managers and can facilitate on-site hazard identification and prevention by semantically reasoning hazards from images and listing corresponding mitigations.
keywords: سل | مدیریت | آموزش مبتنی بر وی چت | پزشکان روستایی | چین | Tuberculosis | Management | WeChat-based training | Rural doctors | China
مقاله انگلیسی
44 Machine learning: Best way to sustain the supply chain in the era of industry 4:0
یادگیری ماشین: بهترین راه برای حفظ زنجیره تأمین در عصر صنعت 4:0-2021
With the rapidly growing importance in the industries on the adaptation of advanced technologies, the involvement of IT-enabled systems has increased in developing the pathway for the future industry. The learning’s from these technologies becomes paramount for the present industries which gives a sense of belongingness and significance of the industry towards the market. The digital revolution world-wide affected the physical happenings of the events in the manufacturing industries such as the procurement, manufacturing/assembling & distribution of goods. This digital reformation is known as Industry 4.0 which generally means the advancement in the existing business models where all the business operations are interconnected with each other by digital mode (virtual representation based on operations). In this kind of environment, it is being necessary to map all the operations digitally in such a manner so that the physical flows of resources/goods will not suffer at any stage. Machine learning in the present scenario is one of the thrust areas for the researchers and the practitioners. The output in the machine learning process is having many dependencies on the input data such as the functions and characteristics imparted to the machine at the earlier stage. The present paper aptly reflects the thoughts and reflections of present-day industries and the opportunities to express feelings, thoughts, and contribute towards the future industries.© 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the 3rd International Conference on Computational and Experimental Methods in Mechanical Engineering.
Keywords: Machine Learning (ML) | Supply Chain (SC) | Industry 4.0 | Resources utilization | Digital transformation
مقاله انگلیسی
45 Application of green supply chain management in the oil Industries: Modeling and performance analysis
کاربرد مدیریت زنجیره تامین سبز در صنایع نفت: مدل سازی و تحلیل عملکرد-2021
Environmental concerns relating to production affairs have made various organizations use green practices in different processes of supply chain, because the green supply chain management (GSCM) is considered as an important organizational philosophy to decrease environmental risks and as a preventive approach in order to increase environmental performance and achievement of competitive advantages for organizations. The purpose of the present article is to design an interactive model for the practices of GSCM and its application to clustering oil industries for analyzing their green performance. Therefore, the literature was studied and a total of fifteen practices were obtained using experts’ opinions in academic and oil industry professionals. In next, the fuzzy interpretative structural modeling (FISM) approach was utilized so as to determine the relationship between the practices through considering the linguistic ambiguities of judgments and designing the structural model. The existing relationships within the structural model were studied and tested by means of structural equation modeling (SEM). After that, the relative importance of each practice was calculated by applying fuzzy analysis network process (FANP). In the next, the oil industries were categorized in two clusters using the K-means algorithm aggregated to the particle swarm optimization algorithm. Results of the present study showed that ‘‘legal requirements and regulations”, ‘‘intra-organizational environmental management”, ‘‘green design” and ‘‘green technology” are of root and influential practices with relatively more importance than others; in addition, it was cleared that the first cluster industries have high performance whereas the second ones have medium performance from the viewpoint of considering the practices of GSCM. Finally, the discriminant function designed to forecasting environment performance of the oil industries and member- ship to clusters for each of them.© 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Web International Conference on Accelerating Innovations in Material Science – 2020.
Keywords: Green Supply Chain Management | Oil industries | Fuzzy interpretative structural modeling | Kmeans | Particle swarm optimization | Clustering | Discriminant analysis
مقاله انگلیسی
46 Stages of Knowledge Representation on the Example of the Typology of Interdisciplinarity: Philosophical Aspects
هیچ یک-2021
It is suggested, when creating knowledge management mechanisms to avoid any extremes in their presentation: various "centrisms", hypertrophy in the use of both mathematical and verbal-meaningful knowledge. It is shown that it is important to observe the principle of "ethics of engagement ", which can be implemented on the basis of a productive interdisciplinary synthesis. The stages of knowledge presentation are considered on the basis of the typology of interdisciplinarity. It is argued that the stage of semantisation (conceptualization) of knowledge representation, when creating control systems, should be preceded by the stage of ontologization. It enhances the distinctiveness of knowledge representation. The stage of ontologization is necessary for the construction of more detailed explanatory constructions, due to the greater formalization of the ontological representation, in comparison with the stage of semantisation. It is assumed that the taxonomy stage can become the basis for the ontologization of knowledge representation, for example, in knowledge engineering.
Keywords: ethics of engagement | knowledge representation | typology of interdisciplinarity semantisation (conceptualization) | ontologization and taxonomization stages
مقاله انگلیسی
47 Smart sensors network for accurate indirect heat accounting in apartment buildings
سنسورهای هوشمند شبکه برای حسابداری دقیق غیر مستقیم در ساختمان های آپارتمان-2021
A new method for accurate indirect heat accounting in apartment buildings has been recently developed by the Centre Suisse d’Electronique et de Microtechnique (CSEM). It is based on a data driven approach aimed to the smart networking of any type of indirect heat allocation devices, which can provide, for each heat delivery point of an apartment building, measurements or es- timations of the temperature difference between the heat transfer fluid and the indoor environ- ment. The analysis of the data gathered from the devices installed on the heating bodies, together with the measurements of the overall building heat consumption provided by direct heat metering, allows the evaluation of the characteristic thermal model parameters of heating bodies at actual installation and working conditions. Thus overcoming the negative impact on accuracy of conventional indirect heat accounting due to off-design operation, in which these measurement systems normally operate. The method has been tested on conventional heat cost allocators (HCA), and on innovative smart radiator thermostatic valves developed by CSEM. The evaluations were carried out at the centralized heating system mock-up of the Istituto Nazionale di Ricerca Metrologica (INRIM), and also in a real building in Neuchatel, Switzerland. The method has proven to be an effective tool to improve the accuracy of indirect heat metering systems; compared to conventional HCA systems, the error on the individual heating bill is reduced by 20%–50%.
keywords: شبکه سنسورهای هوشمند | حسابداری غیر مستقیم | اندازه گیری حرارت | مخزن هزینه های حرارتی | سیستم های گرمایش متمرکز | Smart sensors network | Indirect heat accounting | Heat metering | Heat cost allocators | Centralized heating systems
مقاله انگلیسی
48 A verb-frame frequency account of constraints on long-distance dependencies in English
یک حساب فرکانس فعل از محدودیت‌های وابستگی‌های فاصله‌ای طولانی در زبان انگلیسی-2021
Going back to Ross (1967) and Chomsky (1973), researchers have sought to understand what conditions permit long-distance dependencies in language, such as between the wh-word what and the verb bought in the sentence ‘What did John think that Mary bought?’. In the present work, we attempt to understand why changing the main verb in wh-questions affects the acceptability of long-distance dependencies out of embedded clauses. In particular, it has been claimed that factive and manner-of-speaking verbs block such dependencies (e.g., ‘What did John know/whisper that Mary bought?’), whereas verbs like think and believe allow them. Here we provide 3 acceptability judgment experiments of filler-gap constructions across embedded clauses to evaluate four types of accounts based on (1) discourse; (2) syntax; (3) semantics; and (4) our proposal related to verb-frame frequency. The patterns of acceptability are most simply explained by two factors: verb-frame frequency, such that de- pendencies with verbs that rarely take embedded clauses are less acceptable; and construction type, such that wh-questions and clefts are less acceptable than declaratives. We conclude that the low acceptability of filler-gap constructions formed by certain sentence complement verbs is due to infrequent linguistic exposure.
keywords: پردازش حکم | اثرات فرکانس | وابستگی های راه دور | جزایر نحوی | Sentence processing | Frequency effects | Long-distance dependencies | Syntactic islands
مقاله انگلیسی
49 Knowledge reuse for ontology modelling in Maintenance and Industrial Asset Management
استفاده از دانش برای مدل سازی هستی شناسی در مدیریت نگهداری و مدیریت دارایی صنعتی-2021
Maintenance and Industrial Asset Management (AM) are fundamental business processes in guaranteeing the availability of physical assets at minimum risk and cost, while balancing the interests of several stakeholders. To reach operational excellence, intra- and inter-enterprise interoperability of systems is needed to support infor- mation management and integration between several involved parties. To this end, ontology engineering is relevant since it supports interoperability at technical and semantic levels. However, ontology modelling methodologies are varied, and several best practices exist, amongst which knowledge reuse. Nevertheless, reusing extant knowledge is not completely exploited so far, causing a heterogeneous ensemble of ontologies that are not orchestrated. The present work aims at promoting the adoption of knowledge reuse for ontology modelling in maintenance and AM. Therefore, an extensive review of existing ontologies for the two targeted business processes is performed with a twofold objective: firstly, to realise a cross-industrial ontological com- pendium, and secondly to understand the state of art of ontology modelling in maintenance and AM. To support the adoption of knowledge reuse, this practice is framed in AMODO (Asset Management Ontology Development methOdology). Finally, a laboratory-sized showcase is provided to prove the usefulness of relying on knowledge reuse during the ontology development. The results show that the developed ontology is realised faster and is inherently aligned with established ontologies, towards enterprise systems interoperability. Consequently, maintenance and AM business processes may rely on information management and integration to pursue operational excellence.
keywords: هستی شناسی | استفاده مجدد از دانش | قابلیت همکاری | نگهداری | مدیریت دارایی | Ontology | Knowledge reuse | Interoperability | Maintenance | Asset management
مقاله انگلیسی
50 An entity-relationship model of the flow of waste and resources in city-regions: Improving knowledge management for the circular economy
یک مدل ارتباط برقراری ارتباط از جریان ضایعات و منابع در مناطق شهری: بهبود مدیریت دانش برای اقتصاد دایره ای-2021
Waste and resources management is one of the domains where urban and regional planning can transition to- wards a Circular Economy, thus slowing environmental degradation. Improving waste and resources manage- ment in cities requires an adequate understanding of multiple systems and how they interact. New technologies contribute to improve waste management and resource efficiency, but knowledge silos hinder the possibility of delivering sound holistic solutions. Furthermore, lack of compatibility between data formats and diverse defi- nitions of the same concept reduces information exchange across different urban domains. This paper addresses the challenge of organising and standardising information about waste and resources management in city regions. Given the amount and variety of data constantly captured, data models and standards are a crucial element of Industry 4.0. The paper proposes an Entity-Relationship Model to harmonise definitions and integrate infor- mation on waste and resources management. Furthermore, it helps to formalise the components of the system and their relationships. Semi-structured interviews with government officials, mobile app developers and aca- demics provided insights into the specific system and endorsed the model. Finally, the paper illustrates the translation of the ERM into a relational database schema and instantiates Waste Management and industrial Symbiosis cases in Buenos Aires (ARG) and Helsingborg (SWE) to validate its general applicability. The data model for the Circular Flow of Waste and Resources presented here enhances traditional waste management perspectives by introducing Circular Economy strategies and spatial variables in the model. Thus, this research represents a step towards unlocking the true potential of Industry 4.0.
keywords: شهرهای دایره ای | مدیریت زباله | اقتصاد دایره ای | صنعت 4.0 | مدل ارتباط برق | sql | Circular cities | Waste management | Circular economy | Industry 4.0 | Entity-relationship model | SQL
مقاله انگلیسی
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