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نتیجه جستجو - Web service

تعداد مقالات یافته شده: 50
ردیف عنوان نوع
1 Advanced cyberinfrastructure for intercomparison and validation of climate models
زیرساخت های پیشرفته سایبر برای مقایسه و اعتبار مدل های آب و هوایی-2020
The current routine of comparison and validation in climate science is frequently static and of low efficiency, which hinders evidence-based decision making and scientific confidence. Due to the aggressively increasing resolution, complexity, and associated data volumes of climate models, objectively comparing multiple models and assessing their accuracy against observations is an ever-increasing challenge. We propose an integrated framework for harmonizing state-of-the-art cyberinfrastructure techniques with the user habits formed by longterm familiarity with existing community-oriented software. An open source prototype named COVALI is implemented and used to compare and validate the results of several widely-used climate models and datasets. Our results show that the proposed cyberinfrastructure-based strategy can significantly automate the comparison and validation processes in climate modeling. More importantly, the new strategy retains the existing user habits in the climate community while making it easier for scientists to adopt new technology in their research routine.
Keywords: Model comparison | Model validation | Climate science | Web service | Cyberinfrastructure | Big data
مقاله انگلیسی
2 A cloud-based energy data mining information agent system based on big data analysis technology
سیستم عامل اطلاعات داده کاوی انرژی مبتنی بر ابر مبتنی بر فناوری تجزیه و تحلیل داده های بزرگ-2019
2019 is the first year of 5G and the information flow is growing even more; therefore, data mining technology is one of the key technologies regarding how to find useful information from the vast information flow. This paper aims to develop the cloud-based energy data mining information agent system OntoDMA, as based on the WIAS cloud environment and Big Data analysis technology, which is embedded in a cloud-based active multi-agent system to proactively provide appropriate, real-time, and fast domain information prediction. On one hand, the related technologies for constructing web service platforms are shared; on the other hand, how to widely and seamlessly integrate and support the cloud interaction paradigm handled by the data mining agent system through these technologies is explored. In order to outline the feasibility of the proposed system architecture, a case study is conducted on the energy saving information system, and the relevant R&D results are presented in detail. Then, both the preliminary system R&D interface and experimental verification are illustrated. Finally, the cache performance of the Solutions Pool is increased by 19.82%, the query workload of the Prediction Rules is reduced by 66.51%, and the overall operating time is decreased by 5.21%, which effectively and efficiently relieves the workload on the back-end servo system.
Keywords: Data mining agent systems | Big Data analysis | Web services | Energy saving agent systems
مقاله انگلیسی
3 مروری بر تجمیع دستگاه های مدل سازی اطلاعات ساختمانی (BIM) و اینترنت اشیاء (IoT): وضعیت کنونی و روند آینده
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 13 - تعداد صفحات فایل doc فارسی: 56
تجمیع مدل سازی اطلاعات ساختمانی (BIM) با داده های زمان واقعی(بلادرنگ) دستگاه های اینترنت اشیاء (IoT)، نمونه قوی را برای بهبود ساخت وساز و بهره وری عملیاتی ارائه می دهد. اتصال جریان-های داده های زمان واقعی که بر گرفته از مجموعه هایی از شبکه های حسگرِ اینترنت اشیاء (که این جریان های داده ای، به سرعت در حال گسترش هستند) می باشند، با مدل های باکیفیت BIM، در کاربردهای متعددی قابل استفاده می باشد. با این حال، پژوهش در زمینه ی تجمیع BIM و IOT هنوز در مراحل اولیه ی خود قرار دارد و نیاز است تا وضعیت فعلی تجمیع دستگاه های BIM و IoT درک شود. این مقاله با هدف شناسایی زمینه های کاربردی نوظهور و شناسایی الگوهای طراحی رایج در رویکردی که مخالف با تجمیع دستگاه BIM-IoT می باشد، مرور جامعی در این زمینه انجام می دهد و به بررسی محدودیت های حاضر و پیش بینی مسیرهای تحقیقاتی آینده می پردازد. در این مقاله، در مجموع، 97 مقاله از 14 مجله مربوط به AEC و پایگاه داده های موجود در صنایع دیگر (در دهه گذشته)، مورد بررسی قرار گرفتند. چندین حوزه ی رایج در این زمینه تحت عناوین عملیات ساخت-وساز و نظارت، مدیریت ایمنی و بهداشت، لجستیک و مدیریت ساختمان، و مدیریت تسهیلات شناسایی شدند. نویسندگان، 5 روش تجمیع را همراه با ذکر توضیحات، نمونه ها و بحث های مربوط به آنها به طور خلاصه بیان کرده اند. این روش های تجمیع از ابزارهایی همچون واسط های برنامه نویسی BIM، پایگاه داده های رابطه ای، تبدیل داده های BIM به پایگاه داده های رابطه ای با استفاده از طرح داده های جدید، ایجاد زبان پرس وجوی جدید، فناوری های وب معنایی و رویکردهای ترکیبی، استفاده می کنند. براساس محدودیت های مشاهده شده، با تمرکز بر الگوهای معماری سرویس گرا (SOA) و راهبردهای مبتنی بر وب برای ادغام BIM و IoT، ایجاد استانداردهایی برای تجمیع و مدیریت اطلاعات، حل مسئله همکاری و محاسبات ابری، مسیرهای برجسته ای برای تحقیقات آینده پیشنهاد شده است.
کلمه های کلیدی: مدل سازی اطلاعات ساختمانی (BIM) | دستگاه اینترنت اشیاء (IoT) | حسگرها | ساختمان هوشمند | شهر هوشمند | محیط ساخته شده هوشمند | تجمیع.
مقاله ترجمه شده
4 A technology framework for remote patient care in dermatology for early diagnosis
چارچوبی فناوری برای مراقبت از راه دور بیمار در پوست برای تشخیص زودرس-2019
Healthcare in India has been organized into a three-tier structure. The Primary Health Center (PHC) is a part of the first tier, District Hospitals are in the second tier, and the Tertiary Care Center (TCC) forms the third tier. The PHCs have been set up to meet the healthcare requirements of the rural population, where limited diagnostic facilities are available. The District hospitals have better diagnostic facilities as compared to the PHCs, and the TCCs provide advanced diagnostic facilities. Studies suggest that the rural population is significantly affected by skin diseases and requires services of dermatologists. However, the PHCs do not have the required number of healthcare specialists, including dermatologists to provide treatment for all patients, and they do not have sufficient diagnostic facilities to detect skin related diseases. This lack of healthcare specialists and diagnostic facilities delays intervention and treatments that should be administered to the patients visiting the PHCs. We can enhance the quality of service at the PHCs by providing access to dermatologists and diagnostic facilities through Tele-dermatology, to address and avoid this delay in the onset of intervention. This can be administered to the patient at the rural center with the help of technology. The proposed Tele-dermatology framework connects the PHC to the TCC, equipped with an expert system to provide diagnostic suggestions. Patient details, along with skin lesion images, are acquired at the PHC and then transferred over the Internet to the TCC. The TCC archives the details of a patient and processes the patient image and text data. The expert system at the TCC derives the possible diagnosis of the case being referred. The suggested diagnosis is communicated back to the PHC. Alternatively, the PHC can retrieve the diagnostic suggestions from the TCC even at a later point in time. This diagnostic information would help the health worker at the PHC to begin preventive treatment, to avoid worsening of the patient condition until a physician could attend the case. The implementation of the framework is done using a mobile device and Simple Object Access Protocol (SOAP) based Web services. The developed framework could be a platform for providing suitable services and suggestions at rural health centers comprising mainly PHCs.
Keywords: Rural healthcare | Primary health center | Tele-dermatology | Skin lesion | Web service | Image archival
مقاله انگلیسی
5 A comparative analysis of machine learning models for quality pillar assessment of SaaS services by multi-class text classification of users’ reviews
تجزیه و تحلیل مقایسه ای مدل های یادگیری ماشین برای ارزیابی ستون کیفیت خدمات SaaS با طبقه بندی متن چند طبقه از نظرات کاربران-2019
Software as a Service (SaaS) has emerged as the most widely used of all the current software delivery models. With the growth of edge computing, as SaaS services increasingly become distributed, selecting the best SaaS provider from those available is challenging but it is of critical importance. In the recent past, well-known cloud service providers such as Amazon Web Services and Microsoft have developed frameworks and service quality pillars for cloud applications. However, there are currently no mechanisms for product users to know if and to what extent a service satisfies the defined service pillar. Having such information would enable users to form trustworthy associations in edge computing. In this paper, we address this drawback by adopting a systematic approach of analysing customer reviews related to SaaS products and ascertain to which service quality pillar they refer. We use eleven traditional machine learning classification approaches and a weighted voting ensemble of these classifiers to achieve this task and test the performance of each of them. Since the dataset is unbalanced in terms of sample distribution per class, we use 10-fold cross-validation on the training dataset to determine the best parameters for each machine learning algorithm to achieve optimal performance. Friedman test and Nemenyi’s post hoc test is applied to identify the significant difference among the classifiers performance during cross-validation. Based on the experimental results, a comparative analysis is conducted to identify the best performing machine learning classification model on the SaaS reviews. The results show that the performance of the logistic regression model has a higher performance among the individual classifiers and the weighted voting ensemble shows minimal improvement in overall performance.
Keywords: SaaS | Quality pillars | User reviews | Text classification | Machine learning approaches
مقاله انگلیسی
6 یک چارچوب عامل گرا برای سیستم های نظیر به-نظیر باز بر روی بلاکچین و IPFS
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 11
چکیده: در سال های اخیر نگرانی های فزاینده در مورد سرویس های ابری متمرکز(به عنوان مثال: محرمانگی، حاکمیت، نظارت، امنیت) ضرورت استفاده از فناوری های توزیع شده از قبیل بلاکچین یا IPFS را ایجاد نموده است. این اختراعات دارای مشکلات فنی هستند که تا بروز آنها حل نشده بودند. مدل های فعلی نظیر-به-نظیر نیاز به یک بازبینی برای پوشش طیفی از سیستم های بالقوه دارد تا بتواند به عنوان یک سیستم نظیر-به-نظیر پیاده سازی شود. این مقاله یک چارچوب برای ساختن این سیستم ها ارائه می دهد. این چارچوب یک روش عامل-گرا در یک محیط باز ارائه می دهد که عاملها تنها به قسمتی از داده های سیستم دسترسی دارند. این راهکار دسترسی به داده، اکتشاف داده و اعتماد داده را با متعاملین مختلف را پوشش می دهد. علاوه بر این، این چارچوب یک معماری توزیع شده برای سیستم های باز ارائه می کند که توصیه هایی برای تصمیم گیری در حالت های فناوری بلاکچین و ... فراهم آورده است.
مقاله ترجمه شده
7 OCPMDM: Online computation platform for materials data mining
OCPMDM: پلت فرم محاسبات آنلاین برای داده کاوی مواد-2018
With the rapid development of the Materials Genome Initiative (MGI), scientists and engineers are confronted with the need to conduct sophisticated data analytics in modeling the behaviors of materials. Nowadays, it is inconvenient for material researchers to carry out materials data mining work without an efficient platform for materials machine learning. So, it is meaningful to develop an online platform for material researchers in urgent need of using machine learning techniques by themselves. The typical case study is given to demonstrate the applications of the online computation platform for material data mining (OCPMDM) in our lab: The quantitative structure property relationship (QSPR) model for rapid prediction of Curie temperature of perovskite material can be applied to screen out perovskite candidates with higher Curie temperature than those of training dataset collected from references, efficiently. Material data mining tasks can be implemented via the OCPMDM, which provides powerful tools for material researchers in machine learning-assisted materials design and optimization.
Keywords: Machine learning ، Data mining ، Materials design ، MGI ، Web service
مقاله انگلیسی
8 AWESoME: Big Data for Automatic Web Service Management in SDN
AWESoME: داده های بزرگ برای مدیریت و سرویس های خودکار در SDN-2018
Software defined network (SDN) has enabled consistent and programmable management in computer networks. However, the explosion of cloud services and content delivery networks (CDNs)—coupled with the momentum of encryption—challenges the simple per-flow management and calls for a more comprehensive approach for managing Web traffic. We propose a new approach based on a “per service” management concept, which allows to identify and prioritize all traffic of important Web services, while segregating others, even if they are running on the same cloud platform, or served by the same CDN. We design and evaluate AWESoME, automatic Web service manager, a novel SDN application to address the above problem. On the one hand, it leverages big data algorithms to automatically build models describing the traffic of thousands of Web services. On the other hand, it uses the models to install rules in SDN switches to steer all flows related to the originating services. Using traffic traces from volunteers and operational networks, we provide extensive experimental results to show that AWESoME associates flows to the corresponding Web service in real-time and with high accuracy. AWESoME introduces a negligible load on the SDN controller and installs a limited number of rules on switches, hence scaling well in realistic deployments. Finally, for easy reproducibility, we release ground truth traces and scripts implementing AWESoME core components.
Index Terms: Computer network management, software defined networking, machine learning
مقاله انگلیسی
9 Water utility decision support through the semantic web of things
پشتیبانی تصمیم گیری ابزار آب از طریق وب معنایی اشیا-2018
Urban environments are urgently required to become smarter. However, building advanced applications on the Internet of Things requires seamless interoperability. This paper proposes a water knowledge management platform which extends the Internet of Things towards a Semantic Web of Things, by leveraging the semantic web to address the heterogeneity of web resources. Proof of concept is demonstrated through a decision support tool which leverages both the data-driven and knowledge based programming interfaces of the platform. The solution is grounded in a comprehensive ontology and rule base developed with industry experts. This is instantiated from GIS, sensor, and EPANET data for a Welsh pilot. The web service provides dis coverability, context, and meaning for the sensor readings stored in a scalable database. An interface displays sensor data and fault inference notifications, leveraging the complementary nature of serving coherent lower and higher-order knowledge.
Keywords: Water management ، Decision support tool ، Interoperability ، Big data ، Ontology ، Semantic web ، Internet of things ، Smart water networks
مقاله انگلیسی
10 Ontology-Based Web Service Architecture for Retail Supply Chain Management
هستی شناسی مبتنی بر معماری-وب سرویس برای مدیریت زنجیره تامین خرده فروشی-2018
Service-oriented computing (SOC) technologies provide numerous opportunities and value-added service capabilities that global retail business requires to remain competitive in the market. Initiative to semantic web service provision is playing a crucial role to realize the possibility of heterogenous information systems integration in supply chain. The ability to dynamically discover and invoke a web service is an important aspects of semantic web service-based architecture. An essential part of the service discovery process is the ontology-based semantic web service matchmaking algorithm. This paper presents the key features of an improved matchmaking algorithm to calculate the similarity between concepts on ontology for semantic web service. The matchmaking is taking place in the context of OWL-S (Ontology Web Language for Services) based retail sales management. The paper describes the Semantic Web Service Architecture-II (SWSA-II), which uses a hybrid knowledge-based system; and it consists of Structural Case-Based Reasoning (S-CBR), Rule-Based Reasoning (RBR), and an ontological concept similarity assessment algorithm. Finally, a business scenario is used to demonstrate the functionality of the algorithm.
Keywords: Retail Supply Chain; Service Oriented Computing; Semantic Web Services; Case-Based Reasoning; Rule-Based Reasoning; Ontology Matchmaking Algorithm
مقاله انگلیسی
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