Cameron J. Britton¹, Aaron M. Potretzke¹, Christine Liaw¹, Mohamed E. Ahmed¹, Madeleine G. Manka¹, Kevin M. Wymer¹, Manaf Alom¹, Brian J. Linder¹, Kevin Koo¹, Dane E. Klett^1,2

Canadian Journal of Urology, Vol.30, No.2, pp. 11480-11486, 2023

Abstract Introduction: We aimed to assess the impact of discharge instruction (DCI) readability on 30-day postoperative contact with the healthcare system.
Materials and methods: Utilizing a multidisciplinary team, DCI were modified for patients undergoing cystoscopy, retrograde pyelogram, ureteroscopy, laser lithotripsy, and stent placement (CRULLS) from a 13th grade to a 7th grade reading level. We retrospectively reviewed 100 patients including 50 consecutive patients with original DCI (oDCI) and 50 consecutive patients with improved readability DCI (irDCI). Clinical and demographic data collected including healthcare system contact (communications [phone or electronic message], emergency department [ED], and unplanned clinic visits) within… More >

Sujithra Kanmani^*, Surendiran Balasubramanian

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1439-1454, 2023, DOI:10.32604/csse.2023.029953 - 03 November 2022

Abstract Online reviews significantly influence decision-making in many aspects of society. The integrity of internet evaluations is crucial for both consumers and vendors. This concern necessitates the development of effective fake review detection techniques. The goal of this study is to identify fraudulent text reviews. A comparison is made on shill reviews vs. genuine reviews over sentiment and readability features using semi-supervised language processing methods with a labeled and balanced Deceptive Opinion dataset. We analyze textual features accessible in internet reviews by merging sentiment mining approaches with readability. Overall, the research improves fake review screening by using More >

Sehrish Jamil¹, Salma Noor^1,*, Iftikhar Ahmed², Neelam Gohar¹, Fouzia¹

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 511-524, 2021, DOI:10.32604/iasc.2021.017770 - 16 June 2021

Abstract Significant happenings in terms of spatio-temporal factors are called events. In the digital age, these events and their associated features are scattered in various databases on the Internet. The event data are in heterogeneous formats, which are often not machine-readable. This leads to a lack of unification of event-related knowledge across different domains and results in a research gap in terms of event modeling and representation. Specialized event models are needed to overcome this gap and integrate relevant information of different similar events occurring worldwide. Our research explores the problem of heterogeneity in specialized event… More >

Qirun Wang^1,2, Fujian Zhu^3,4, Yan Leng^3,4, Yongjun Ren^3,4,*, Jinyue Xia⁵

Journal on Internet of Things, Vol.1, No.1, pp. 33-39, 2019, DOI:10.32604/jiot.2019.05898

Abstract With the rapid development of E-commerce and E-government, there are so many electronic records have been produced. The increasing number of electronic records brings about storage difficulties, the traditional electronic records center is difficult to cope with the current fast growth requirements of electronic records storage and management. Therefore, it is imperative to use cloud storage technology to build electronic record centers. However, electronic records also have weaknesses in the cloud storage environment, and one of them is that once electronic record owners or managers lose physical control of them, the electronic records are more More >

Zhijuan Wang^1,2, Xiaobin Zhao^1,2, Wei Song^1,*, Antai Wang³

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 213-225, 2019, DOI:10.32604/cmc.2019.05690

Abstract Readability is a fundamental problem in textbooks assessment. For low re-sources languages (LRL), however, little investigation has been done on the readability of textbook. In this paper, we proposed a readability assessment method for Tibetan textbook (a low resource language). We extract features based on the information that are gotten by Tibetan segmentation and named entity recognition. Then, we calculate the correlation of different features using Pearson Correlation Coefficient and select some feature sets to design the readability formula. Fit detection, F test and T test are applied on these selected features to generate a More >