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.
Bias reduction in the population size estimation of large data sets
کاهش تمایل در برآورد اندازه جمعیت مجموعه داده های بزرگ-2020
Estimation of the population size of large data sets and hard to reach populations can be a significant problem. For example, in the military, manpower is limited and the manual processing of large data sets can be time consuming. In addition, accessing the full population of data may be restricted by factors such as cost, time, and safety. Four new population size estimators are proposed, as extensions of existing methods, and their performances are compared in terms of bias with two existing methods in the big data literature. These would be particularly beneficial in the context of time-critical decisions or actions. The comparison is based on a simulation study and the application to five real network data sets (Twitter, LiveJournal, Pokec, Youtube, Wikipedia Talk). Whilst no single estimator (out of the four proposed) generates the most accurate estimates overall, the proposed estimators are shown to produce more accurate population size estimates for small sample sizes, but in some cases show more variability than existing estimators in the literature.
Keywords: Relative bias | Twitter | Size estimator | Youtube | Random walk sampling
چارچوب حاکمیتی هوش تجاری در دانشگاه: مطالعه موردی دانشگاه دو لا کاستا
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 25
دانشگاه ها و شرکت ها دارای فرآیندهای تصمیم گیری هستند که به آنها اجازه می دهد تا به اهداف سازمانی دست پیدا کنند. در حال حاضر، تحلیل داده ها نقش مهمی در ایجاد دانش، بدست آوردن الگوهای مهم و پیش بینی استراتژی ها ایفا می کنند.این مقاله طراحی چارچوب نظارت هوش تجاری را برای دانشگاه دو لا کاستا ارائه کرده است که به آسانی برای سازمان های دیگر هم قابل استفاده است. برای این منظور، تشخیص انجام شده به منظور شناسایی میزان بلوغ تحلیلی انجام شده است. با استفاده از این چشم انداز، مدلی برای تقویت فرهنگ سازمانی ، زیر ساختارها، مدیریت داده، تحلیل داده و نظارت ارائه شده است.این مدل در بر گیرنده تعریف چارچوب نظارتی، اصول هدایت کننده، استراتژی ها، نهادهای تصمیم گیرنده و نقش ها می باشد. بنابراین، این چارچوب برای استفاده از کنترل های موثر جهت اطمینان از موفقیت پروژه های هوش تجاری و دست یابی به اهداف برنامه توسعه همراه با چسم انداز تحلیلی سازمان ارائه شده است.
کلمات کلیدی: هوش تجاری | نظارت | دانشگاه | تحلیل | تصمیم گیری
|مقاله ترجمه شده|
Implementation of a standardized voiding management protocol to reduce unnecessary re-catheterization - A quality improvement project
اجرای یک پروتکل استاندارد مدیریت تخلیه برای کاهش دوباره کاتتریزاسیون غیر ضروری - یک پروژه بهبود کیفیت-2020
Objective. To design and implement a standardized postoperative voiding management protocol that accurately identifies patients with urinary retention and reduces unnecessary re-catheterization. Methods. A postoperative voiding management protocol was designed and implemented in patients undergoing major, inpatient, non-radical abdominal surgery with a gynecologic oncologist. No patients had epidural catheters. The implemented quality improvement (QI) protocol included: 1) Foley removal at six hours postoperatively; 2) universal bladder scan after the first void; and 3) limiting re-catheterization to patientswith bladder scan volumes N150 ml. A total of 96 patients post-protocol implementation were compared to 52 patients preprotocol. Along with baseline demographic data and timing of catheter removal,we recorded the presence or absence of urinary retention and/or unnecessary re-catheterization and postoperative urinary tract infection rates. Fishers exact test and students t-tests were performed for comparisons. Results. The overall rate of postoperative urinary retention was 21.6% (32/148). The new voiding management protocol reduced the rate of unnecessary re-catheterization by 90% (13.5% vs 2.1%, p = 0.01), without overlooking true urinary retention (23.1% vs 20.8%, p = 0.83). Additionally, there was a significant increase in hospital-defined early discharge prior to 11:00 AM (4.0% vs 22.0%, p = 0.022). There was no difference in the postoperative urinary tract infection rate between the groups (p=1.00). Risk factors associatedwith urinary retention included older age (p b 0.01), use of medications with anticholinergic properties (p b 0.01), and preexisting urinary dysfunction (p b 0.01). Conclusions. Implementation of this new voiding management protocol reduced unnecessary recatheterization, captured and treated true urinary retention, and facilitated early hospital discharge
Keywords: Quality improvement | Bladder voiding | Urinary retention | Postoperative management | Gynecologic Oncology surgery | Urinary tract infection
MISS-D: A fast and scalable framework of medical image storage service based on distributed file system
MISS-D: یک چارچوب سریع و مقیاس پذیر از خدمات ذخیره سازی تصویر پزشکی بر اساس سیستم فایل توزیع شده-2020
Background and Objective Processing of medical imaging big data is deeply challenging due to the size of data, computational complexity, security storage and inherent privacy issues. Traditional picture archiving and communication system, which is an imaging technology used in the healthcare industry, generally uses centralized high performance disk storage arrays in the practical solutions. The existing storage solutions are not suitable for the diverse range of medical imaging big data that needs to be stored reliably and accessed in a timely manner. The economical solution is emerging as the cloud computing which provides scalability, elasticity, performance and better managing cost. Cloud based storage architecture for medical imaging big data has attracted more and more attention in industry and academia. Methods This study presents a novel, fast and scalable framework of medical image storage service based on distributed file system. Two innovations of the framework are introduced in this paper. An integrated medical imaging content indexing file model for large-scale image sequence is designed to adapt to the high performance storage efficiency on distributed file system. A virtual file pooling technology is proposed, which uses the memory-mapped file method to achieve an efficient data reading process and provides the data swapping strategy in the pool. Result The experiments show that the framework not only has comparable performance of reading and writing files which meets requirements in real-time application domain, but also bings greater convenience for clinical system developers by multiple client accessing types. The framework supports different user client types through the unified micro-service interfaces which basically meet the needs of clinical system development especially for online applications. The experimental results demonstrate the framework can meet the needs of real-time data access as well as traditional picture archiving and communication system. Conclusions This framework aims to allow rapid data accessing for massive medical images, which can be demonstrated by the online web client for MISS-D framework implemented in this paper for real-time data interaction. The framework also provides a substantial subset of features to existing open-source and commercial alternatives, which has a wide range of potential applications.
Keywords: Hadoop distributed file system | Data packing | Memory mapping file | Message queue | Micro-service | Medical imaging
A robust co-state predictive model for energy management of plug-in hybrid electric bus
یک مدل پیش بینی شده مشترک قدرتمند برای مدیریت انرژی اتوبوس برقی هیبریدی پلاگین-2020
This paper proposes a robust co-state predictive model for Pontryagin’s Minimum Principle (PMP)-based energy management of plug-in hybrid electric bus (PHEB). The main innovation is that the robust costate predictive model is only expressed by a simplified formula. Moreover, it is exclusively designed by the Design For Six Sigma (DFSS) method in consideration of noises of driving cycles and stochastic vehicle mass. Because the DFSS strives to minimize the weighted sum of mean and standard deviation of fuel consumption, the proposed strategy can simultaneously improve the fuel economy of the PHEB and its robustness. The DFSS results show that the coefficients of the robust co-state predictive model can be found; the simulation results demonstrate that the proposed strategy has similar fuel economy to dynamic programming (DP); the hardware-in-loop (HIL) results demonstrate that the proposed strategy has good real-time control performance, and can averagely improve the fuel economy by 35.19% compared to a rule-based control strategy.
Keywords: Plug-in hybrid electric bus | Energy management | PMP | Co-state predictive model | Design for six sigma
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
Cooperative control strategy for plug-in hybrid electric vehicles based on a hierarchical framework with fast calculation
استراتژی کنترل تعاونی برای وسایل نقلیه برقی هیبریدی پلاگین بر اساس یک چارچوب سلسله مراتبی با محاسبه سریع-2020
Developing optimal control strategies with capability of real-time implementation for plug-in hybrid electric vehicles (PHEVs) has drawn explosive attention. In this study, a novel hierarchical control framework is proposed for PHEVs to achieve the instantaneous vehicle-environment cooperative control. The mobile edge computation units (MECUs) and the on-board vehicle control units (VCUs) are included as the distributed controllers, which enable vehicle-environment cooperative control and reduce the computation intensity on the vehicle by transferring partial work from VCUs to MECUs. On this basis, a novel cooperative control strategy is designed to successively achieve the energy management planned by the iterative dynamic programming (IDP) in MECUs and the energy utilization management achieved by the model predictive control (MPC) algorithm in the VCU. The performance of raised control strategy is validated by simulation analysis, highlighting that the cooperative control strategy can achieve superior performance in real-time application that is close to the global optimization results solved offline.
Keywords: Cooperative control strategy | Hierarchical framework | Iterative dynamic programming (IDP) | Model predictive control (MPC) | Plug-in hybrid electric vehicles (PHEVs)
Cellular automata Markov chain model based deforestation modelling in the pastoral and agro-pastoral areas of southern Ethiopia
مدل سازی زنجیره مارکوف ماشین سلولی مبتنی بر مدلسازی جنگل زدایی در مناطق روحانی و کلیسایی در جنوب اتیوپی-2020
Permanent conversion of woodland to large-scale commercial agriculture, pastures or urban areas and temporary or partial removal of indigenous trees for shifting cultivation and selective logging remained major environmental challenges in the tropical region. Cognizant of the environmental changes prevailing in the pastoral and agro-pastoral areas of Southern Ethiopia, we have examined the past conversion of woodland to other land uses through the analysis of Landsat Multi-spectral scanner (MSS) 1973, Thematic Mapper(TM) 1986, Enhanced Thematic Mapper (ETMþ) 2003, Operational Land Imagery (OLI) 2017 and then projected the future change in land use/cover (LUC) as well. We have employed Cellular Automata Markov chain model to simulate and predict LUC changes between 2017 and 2060. Four spatial driver variables such as distance to road and settlement, slope and elevation were used to run the simulation. Prior to the prediction, we have simulated the LUC of 2017 using transition potential maps of 2003 and transition matrix between 1973 and 2003. The predictive power of the model was then examined by comparing the reference and simulated LUC maps of 2017and also using the kappa index. A good correlation was obtained between the reference and simulated LUC maps of 2017. In addition, the computed kappa index was above 0.9, which implies that the model is effective in predicting change in LUC. The analysis result revealed that in the entire monitoring period (1973–2017) the area lost 89,875 ha of woodland. The loss is expected to continue during the period 2017–2060, with an estimated loss of 32,423 ha of woodland, if a proper measure is not taken against the continuous loss of woodland. Thus, relentless efforts are needed to rehabilitate the already degraded land and also minimize the potential loss of woodland in the future through the implementation of conservation – livelihood approach, REDD þ project, and sustainable land use management strategies.
Keyterms: Deforestation | Kappa coefficient | CA-Markov | Woodland
A framework for extracting urban functional regions based on multi prototype word embeddings using points-of-interest data
چارچوبی برای استخراج مناطق عملکردی شهری بر اساس تعبیه چند کلمه نمونه اولیه با استفاده از داده های مورد علاقه-2020
Many studies are in an effort to explore urban spatial structure, and urban functional regions have become the subject of increasing attention among planners, engineers and public officials. Attempts have been made to identify urban functional regions using high spatial resolution (HSR) remote sensing images and extensive geodata. However, the research scale and throughput have also been limited by the accessibility of HSR remote sensing data. Recently, big geo-data are becoming increasingly popular for urban studies since research is still accessible and objective with regard to the use of these data. This study aims to build a novel framework to provide an alternative solution for sensing urban spatial structure and discovering urban functional regions based on emerging geo-data – points of interest (POIs) data and an embedding learning method in the natural language processing (NLP) field. We started by constructing the intraurban functional corpus using a centercontext pairs-based approach. A word embeddings representation model for training that corpus was used to extract multiprototype vectors in the second step, and the last step aggregated the functional parcels based on an introduced spatial clustering method, hierarchical density-based spatial clustering of applications with noise (HDBSCAN). The clustering results suggested that our proposed framework used in this study is capable of discovering the utilization of urban space with a reasonable level of accuracy. The limitation and potential improvement of the proposed framework are also discussed.
Keywords: Urban functional regions | Word embeddings | Points-of-interest | Spatial clusters
Utilizing courageous dialogue to support minority and disadvantaged background nursing students
استفاده از گفتگوی شجاعانه برای حمایت از دانشجویان اقلیت و محروم پرستاری-2020
Background: Nursing students from historically underrepresented ethnic minorities and disadvantaged background (HUREM-DB) groups often face barriers such as a lack of consistent financial resources, fewer professional role models, bias, and micro-inequities. Utilizing a multifaceted approach for support can be crucial to enhancing student success. Purpose of the project: MENTORS2 mitigates some of the challenges for HUREM-DB nursing students with educational, cultural, social, and financial resources. Courageous dialogue (CD) was one required activity of MENTORS2 and included topics such as stress management, time management, and honors project preparation. Implementation of the project: Courageous dialogue sessions were conducted with 56 HUREM-DB undergraduate nursing students enrolled in a baccalaureate program. The number of evaluations submitted for a session averaged 17 (range 7–36). Courageous dialogue sessions allowed students to express views in a safe environment with opportunities for peer support, role modeling, open discussion, and problem solving. Project outcomes: Student evaluations reflected an appreciation of the opportunity to share experiences and learn new skills, knowledge, and approaches to aid their success in nursing school and perhaps their entry into the profession of nursing. Conclusion: Courageous dialogue can be an important part of a comprehensive strategy to support HUREM-DB nursing students academically, socially, and professionally.
Keywords: Courageous dialogues | Disadvantaged background | Ethnic minority | Nursing student