با سلام خدمت کاربران عزیز، به اطلاع می رساند ترجمه مقالاتی که سال انتشار آن ها زیر 2008 می باشد رایگان بوده و میتوانید با وارد شدن در صفحه جزییات مقاله به رایگان ترجمه را دانلود نمایید.
An overview of longshore sediment transport on the Brazilian coast✩
مروری بر حمل و نقل رسوب longshore در سواحل برزیل-2020
The present study investigates the wave behavior and the longshore sediment transport rate on the Brazilian continental shelf, using a computational model and four different formulations, for the period between 1979–2015. The average significant wave height is substantially variable along the study region, with the largest values occurring in southern Brazil, whereas the smaller values occur in northern Brazil. The longshore sediment transport rates are well within the range of values presented in previous works and indicate which method performs best in estimating annual mean rates of sediment transport. The highest sediment transport rates were found in the sector situated within the northern coast of the Bahia state and the Alagoas state, reaching 460 000 m3 year−1. On the other hand, the opposite was found between the Rio de Janeiro and southern Bahia coast, where the smallest transport rates occurred with a global average of 109 000 m3 year−1. Additionally, it is important to emphasize that small variations in the wave incidence angle may cause significant changes in the longshore drift of sediments, favoring the occurrence of zones of convergence and divergence along the coast. The novel results presented for the entire Brazilian shore contribute to the literature related to wave and sediment transport along the Brazilian coast and can be useful for future engineering projects that consider the sustainable management of the coastal zone.
Keywords: Numerical modeling | TOMAWAC | CERC | Kamphuis | Longshore sediment transport | Coastal zone
Efficacy and safety of oral and inhalation commercial beta-glucan products: Systematic review of randomized controlled trials
اثربخشی و ایمنی محصولات بتا گلوکان تجاری و خوراکی استنشاق: مرور سیستماتیک کارآزمایی کنترل شده تصادفی-2020
Background & aims: Beta-glucans are advertised as biologically active compounds, with various health claims.We aimed to summarize results about efficacy and safety of commercial oral and inhalation betaglucan products on human health from randomized controlled trials (RCTs). Methods: We conducted systematic review of RCTs. We searched MEDLINE, CENTRAL and ClinicalTrials. gov. Any commercial product, any types of participants and any health-related outcomes were eligible. Two authors independently screened studies and extracted data. Cochrane risk of bias tool was used. This review did not have any extramural funding. Registration: PROSPERO record no. 42016043539. Results: We included 30 RCTs that were conducted on healthy or ill participants. Most of the trials reported beneficial effect of beta-glucan, but among the 105 different outcome domains and measures that were used, only three could be considered clinically relevant, while others were various biomarkers and surrogate outcomes such as complete blood count. Included studies on average had 33 participants per study arm, high or unclear risk of bias of at least one domain, and only half of them reported data for safety. More than half of trials that reported source of funding indicated commercial sponsorship from producers of beta-glucan. Only five RCTs reported trial registration. Conclusions: Commercial beta-glucan products were studied in a number of RCTs whose results can be considered only as preliminary, as they used small number of participants and surrogate outcomes. The quality of many studies was poor and further research and trials on bigger population should be performed before a final conclusion can be made.
Keywords: Beta-glucan | Systematic review | Evidence | Randomized controlled trial | Research waste
Challenges and recommended technologies for the industrial internet of things: A comprehensive review
چالش ها و فن آوری های پیشنهادی برای اینترنت اشیا صنعتی: مرور جامع-2020
Physical world integration with cyber world opens the opportunity of creating smart environments; this new paradigm is called the Internet of Things (IoT). Communication between humans and objects has been extended into those between objects and objects. Industrial IoT (IIoT) takes benefits of IoT communications in business applications focusing in interoperability between machines (i.e., IIoT is a subset from the IoT). Number of daily life things and objects connected to the Internet has been in increasing fashion, which makes the IoT be the dynamic network of networks. Challenges such as heterogeneity, dynamicity, velocity, and volume of data, make IoT services produce inconsistent, inaccurate, incomplete, and incorrect results, which are critical for many applications especially in IIoT (e.g., health-care, smart transportation, wearable, finance, industry, etc.). Discovering, searching, and sharing data and resources reveal 40% of IoT benefits to cover almost industrial applications. Enabling real-time data analysis, knowledge extraction, and search techniques based on Information Communication Technologies (ICT), such as data fusion, machine learning, big data, cloud computing, blockchain, etc., can reduce and control IoT and leverage its value. This research presents a comprehensive review to study state-of-the-art challenges and recommended technologies for enabling data analysis and search in the future IoT presenting a framework for ICT integration in IoT layers. This paper surveys current IoT search engines (IoTSEs) and presents two case studies to reflect promising enhancements on intelligence and smartness of IoT applications due to ICT integration.
Keywords: Industrial IoT (IIoT) | Searching and indexing | Blockchain | Big data | Data fusion Machine learning | Cloud and fog computing
Prescriptive analytics: Literature review and research challenges
تجزیه و تحلیل تجربی: مرور ادبیات و چالش های تحقیقاتی-2020
Business analytics aims to enable organizations to make quicker, better, and more intelligent decisions with the aim to create business value. To date, the major focus in the academic and industrial realms is on descriptive and predictive analytics. Nevertheless, prescriptive analytics, which seeks to find the best course of action for the future, has been increasingly gathering the research interest. Prescriptive analytics is often considered as the next step towards increasing data analytics maturity and leading to optimized decision making ahead of time for business performance improvement. This paper investigates the existing literature pertaining to prescriptive analytics and prominent methods for its implementation, provides clarity on the research field of prescriptive analytics, synthesizes the literature review in order to identify the existing research challenges, and outlines directions for future research.
Keywords: Analytics | Prescriptive analytics | Business analytics | Big data | Literature review
A review of hierarchical control for building microgrids
مروری بر کنترل سلسله مراتبی برای میکرو گریدهای ساختمان-2020
Building microgrids have emerged as an advantageous alternative for tackling environmental issues while enhancing the electricity distribution system. However, uncertainties in power generation, electricity prices and power consumption, along with stringent requirements concerning power quality restrain the wider development of building microgrids. This is due to the complexity of designing a reliable and robust energy management system. Within this context, hierarchical control has proved suitable for handling different requirements simultaneously so that it can satisfactorily adapt to building environments. In this paper, a comprehensive literature review of the main hierarchical control algorithms for building microgrids is discussed and compared, emphasising their most important strengths and weaknesses. Accordingly, a detailed explanation of the primary, secondary and tertiary levels is presented, highlighting the role of each control layer in adapting building microgrids to current and future electrical grid structures. Finally, some insights for forthcoming building prosumers are outlined, identifying certain barriers when dealing with building microgrid communities.
Index Terms: Electricity market | Energy management system | Optimisation algorithms | Renewable energy source | Prosumer
An internet of energy framework with distributed energy resources, prosumers and small-scale virtual power plants: An overview
اینترنت چارچوب انرژی با منابع انرژی توزیع شده ، پیشرانها و نیروگاه های مجازی در مقیاس کوچک: یک مرور کلی-2020
Current power networks and consumers are undergoing a fundamental shift in the way traditional energy systems were designed and managed. The bidirectional peer-to-peer (P–P) energy transactions pushed passive consumers to be prosumers. The future smart grid or the internet of energy (IoE) will facilitate the coordination of all types of prosumers to form virtual power plants (VPP). The paper aims to contribute to this growing area of research by accumulating and summarizing the significant ideas of the integration of distributed prosumers and small-scale VPP to the internet of energy (IoE). The study also reports the characteristics of IoE in comparison to the traditional grid and offers some valuable insights into the control, management and optimization strategies of prosumers, distributed energy resources (DERs) and VPP. As bidirectional P–P energy transaction by the prosumers is a crucial element of IoE, their management strategies including various demand-response approach at the customers’-levels are systematically summarized. The integration of DERs and prosumers to the VPP considering their functions, infrastructure, type, control objectives are also reviewed and summarized. Various optimization techniques and algorithm, and their objectives functions and the types of mathematical formulation that are used to manage the DERs and VPP are discussed and categorized systematically. Finally, the factors which affect the integration of DERs and prosumers to the VPP are identified.
Keywords: Bidirectional energy transactions | Distributed energy resources | Energy management | Internet of energy | Optimization techniques | Prosumers | Virtual power plant
Review on performance assessment of phase change materials in buildings for thermal management through passive approach
مروری بر ارزیابی عملکرد مواد تغییر فاز در ساختمانها برای مدیریت حرارتی از طریق رویکرد غیرفعال-2020
Latent heat energy storage (LHES) systems using phase change materials (PCMs) are well known for its excellent thermal energy storage and release during melting and solidifications respectively. PCMs can be efficiently deployed in applications where significant temperature difference exists in the system for intermittent thermal energy storage. Several research contributions has been made on integrating PCMs in buildings for thermal management, as it enhances building thermal inertia, reduces maximum heat flux, shifts peak energy demand, reduces temperature fluctuations of air, etc., owing to its isothermal behavior and high energy storage density during phase change. Results of several research articles reveal that incorporation of PCM in buildings could significantly improve indoor comfort conditions and reduce energy demand of Heating ventilation and air conditioning (HVAC) systems, provided appropriate PCM selection, encapsulation methods, location deployed etc. This review paper is devoted to elucidate various facts attributing PCM integration in buildings for thermal management through passive approach. The facts includes performance of PCMs in buildings in terms of heat gain reduction, temperature attenuation, peak energy demand shifting and energy saving potential, encapsulation deployed, are discussed and presented in order to expedite the interpretation for future researchers, who took their research work in the field of building thermal energy management.
Keywords: Phase change material | Passive approach | Thermal energy management | PCM Encapsulation | Buildings
Review of methods used to estimate the sky view factor in urban street canyons
مروری بر روشهای مورد استفاده برای تخمین عامل نمای آسمان در دره های خیابانی شهری-2020
The sky view factor (SVF) is the ratio of the visible sky area of a point in space to the total sky area. It provides the relationship between the visible sky area and covered surroundings, such as by buildings or street trees. The SVF has been widely used as a key parameter in urban climate research and urban planning practices. Significant research has taken place in the past decades on methods of calculating/estimating SVFs to improve their accuracy and efficiency. This review lists the methods used to calculate/estimate SVFs including geometric methods, fish-eye photographical method, Global Positioning System methods, simulation methods based on 3D city models or digital surface models, and big data approaches using street view images. We stress the principles, input data, application, accuracy and efficiency of each method. This review is meaningful for climatologists in solar radiation modeling and energy balance modeling fields, as well as for urban planners in the development of design guidelines to improve outdoor thermal comfort in the urban environment.
Keywords: Sky view factor | Urban street canyon | Aspect ratio | Street panoramic images | Urban planning
Manufacturing big data ecosystem: A systematic literature review
ساخت اکوسیستم داده های بزرگ: مروری بر ادبیات سیستماتیک-2020
Advanced manufacturing is one of the core national strategies in the US (AMP), Germany (Industry 4.0) and China (Made-in China 2025). The emergence of the concept of Cyber Physical System (CPS) and big data imperatively enable manufacturing to become smarter and more competitive among nations. Many researchers have proposed new solutions with big data enabling tools for manufacturing applications in three directions: product, production and business. Big data has been a fast-changing research area with many new opportunities for applications in manufacturing. This paper presents a systematic literature review of the state-of-the-art of big data in manufacturing. Six key drivers of big data applications in manufacturing have been identified. The key drivers are system integration, data, prediction, sustainability, resource sharing and hardware. Based on the requirements of manufacturing, nine essential components of big data ecosystem are captured. They are data ingestion, storage, computing, analytics, visualization, management, workflow, infrastructure and security. Several research domains are identified that are driven by available capabilities of big data ecosystem. Five future directions of big data applications in manufacturing are presented from modelling and simulation to realtime big data analytics and cybersecurity.
Keywords: Smart manufacturing | Big data | Cloud computing | Cloud manufacturing | Internet of things | NoSQL
A survey of feature modeling methods: Historical evolution and new development
مرور روشهای مدل سازی ویژگی ها: تکامل تاریخی و توسعه جدید-2020
Initially developed for geometric representation, feature modeling has been applied in product design and manufacturing with great success. With the growth of computer-aided engineering (CAE), computer-aided process planning (CAPP), computer-aided manufacturing (CAM), and other applications for product engineering, the definitions of features have been mostly application-driven. This survey briefly reviews feature modeling historical evolution first. Subsequently, various approaches to resolving the interoperability issues during product lifecycle management are reviewed. In view of the recent progress of emerging technologies, such as Internet of Things (IoT), big data, social manufacturing, and additive manufacturing (AM), the focus of this survey is on the state of the art application of features in the emerging research fields. The interactions among these trending techniques constitute the socio-cyber-physical system (SCPS)-based manufacturing which demands for feature interoperability across heterogeneous domains. Future efforts required to extend feature capability in SCPS-based manufacturing system modeling are discussed at the end of this survey.
Keywords: Feature modeling | Feature ontology | Feature interoperability | Engineering informatics | Socio-cyber-physical system