Effectiveness of RSS feed item duplication detection using word matching

Users of feed aggregators know that duplicated articles are found occasionally on the feeds they subscribe to. It can be time consuming to read all articles and stumble upon duplicated items they have already read. Our work here is to determine the effectiveness of using basic word matching to remove duplicated items and only show the most relevant item, thus saving readers’ time. The method described in this paper to remove duplicates involves word matching heuristics with an appropriate matching percentage. The duplicated feeds are then ranked to only display the highest ranked article. Ranking is done using the number of search items found on the titles of the news feeds where the highest number returned will be considered the highest ranked article. Using Malaysian online news feeds, our method found that with a matching percentage of 40%, our method will be able to minimize duplicates effectively with minimal errors. We did further empirical studies using 9 technology blog feeds over a longer period to provide us with a better averaging results. The matching percentage obtained is also within the same quantum. The method described here has a low overhead in terms of processing for the duplicates and with careful selection of matching percentage, the system will effectively remove the majority of duplicate

Public perception of flood risks in Klang Valley, Malaysia: A case study

Floods are becoming a major global concern as these disasters become more severe and frequent. This is no exception to Malaysia, as the trend of flood occurrences is increasing year by year. This study aimed to understand the public perception of the flood risks in Klang Valley, focusing on Kuala Lumpur and Selangor metropolitan areas. A total of 100 respondents participated in this survey via online questionnaire distribution. There are four variables tested in this survey, where factors on environmental concern and anticipating risk have moderate influence on the perception and awareness of flood risk. Both environmental concern (ß = 0.378, p < 0.000) and anticipating risk (ß = 0.349, p< 0.000) were the only correlations that were statistically significant. It was found that emotional impact (ß = 0.058, p < 0.511) and effort to contribute (ß = 0.148, p < 0.077) did not significantly predict awareness of flood risks. Further studies are needed to truly grasp the public’s perception of flood risk in Kuala Lumpur and Selangor

Factors that influence consumers when applying for debit cards.

This study aims to identify the various factors which influence consumers when deciding whether to apply for a debit card and the relative importance of the respective factors on the decision making process

A splitting moving mesh method for reaction-diffusion equations of quenching type

10.1016/j.jcp.2005.11.019Journal of Computational Physics2152757-777JCTP

Factors Influencing Continuous Intention to Use Mobile Commerce Applications during the Covid-19 Pandemic

This study examines the factors influencing continuous intention to use mobile commerce applications in Malaysia during the COVID-19 pandemic. Drawing on the Unified Theory of Use and Acceptance of Technology (UTAUT), Task-Technology Fit Model (TTF), and Expectancy Confirmation Model (ECM), the multiple regression analysis indicated that Performance Expectancy (PE), Social Influence (SI), Perceived Task-Technology Fit (TTF), and Hedonic Value (HV) positively affect continuous intention to use mobile commerce applications. Contrariwise, Effort Expectancy (EE), Trust (TR), Confirmation (COF), and Perceived Risk (PR) did not predict continuous intention to use mobile commerce applications. Theoretical and practical implications are discussed in this paper

Ultralightweight mutual authentication RFID protocol for blockchain enabled supply chains

Previous research studies mostly focused on enhancing the security of radio frequency identification (RFID) protocols for various RFID applications that rely on a centralized database. However, blockchain technology is quickly emerging as a novel distributed and decentralized alternative that provides higher data protection, reliability, immutability, transparency, and lower management costs compared with a conventional centralized database. These properties make it extremely suitable for integration in a supply chain management system. In order to successfully fuse RFID and blockchain technologies together, a secure method of communication is required between the RFID tagged goods and the blockchain nodes. Therefore, this paper proposes a robust ultra-lightweight mutual authentication RFID protocol that works together with a decentralized database to create a secure blockchain-enabled supply chain management system. Detailed security analysis is performed to prove that the proposed protocol is secure from key disclosure, replay, man-in-the-middle, de-synchronization, and tracking attacks. In addition to that, a formal analysis is conducted using Gong, Needham, and Yahalom logic and automated validation of internet security protocols and applications tool to verify the security of the proposed protocol. The protocol is proven to be efficient with respect to storage, computational, and communication costs. In addition to that, a further step is taken to ensure the robustness of the protocol by analyzing the probability of data collision written to the blockchain.</p

Face Mask Wearing Detection: A Comparative Analysis

The COVID-19 pandemic has had a tremendous influence around the globe, impacting nearly every element of daily life. It has resulted in widespread illness and death, economic disruption, and changes in societal norms. Governments and organizations have applied various measures to slow the spread of the virus and mitigate its impacts. Among the most important mechanisms is the use of face masks to prevent the transmission and infection of COVID-19. This paper investigates and analyzes different machine learning (ML) methods to execute the classification task of categorizing faces into three classes: wearing masks, not wearing masks, or wearing masks improperly. The preprocessed and augmented dataset used in the study contains 4801 images with the dimension (50, 50, 3) and there are approximately 1500 faces for each class. According to the experimental results, convolutional neural networks (CNNs) can achieve 87% accuracy in classifying faces. These results indicate that CNNs outperform other ML methods, such as random forest, Naïve Bayes, and support vector machine

Changing patient profile, hearing aid use and disability among first-time hearing aid users in Singapore over a decade

Objectives: To examine the time trends in demographics, hearing characteristics, hearing aid (HA) choices, usage and patient-reported disability among first-time HA users in Singapore over a decade. Design: Cross-sectional study. Study sample: 1052 subjects issued with HAs at a tertiary hospital from 2004 to 2013. Results: An increase in number of first time HA users were seen from 2004 to 2013. Although mean age did not change significantly, the proportion of older adults (>80 years) being fitted increased (p for trend ¼ 0.033). Inflation adjusted cost of HAs rose over time (p 7 hours daily (AOR ¼ 0.45, 95% CI 0.34–0.59) was seen. Conclusion: From 2004 to 2013, there was a positive trend towards HA uptake in Singapore. Bilateral HA uptake increased while customisable in ear type of HA use decreased. While hearing disability showed a decreasing trend, HA usage remained suboptimal. Abbreviations: BTE: Behind the ear; CIC: Completely in the canal; HAE: Hearing aid evaluation; HAF: Hearing aid fitting; ITC: In the canal; ITE: In the ear; PHAF: Post hearing aid fitting; RIC: Receiver in canalAccepted versionThis work was supported by the National Healthcare Group (NHG) Clinician Scientist Career Scheme under grant (CSCS 2013/00325)

Hearing impairment and hearing aid usage in Singapore

<p><i>Objective</i>: To examine the epidemiological and audiological profile, pattern of hearing aid (HA) fitting and usage among HA users in Singapore. <i>Design</i>: Retrospective cross-sectional study. <i>Study sample</i>: Cohort of 1068 subjects issued with HAs at a tertiary hospital between 2001 and 2013. <i>Results</i>: Mean age was 70 years with 50.8% male. Mean hearing loss (HL) was 63.1 dB and 69.5% had at least moderate-severe HL. Sensorineural HL was present in 66.4% and 69.8% had symmetrical HL. “Behind-the-Ear” HAs were cheaper than “In-Ear” HAs. Standard “Behind-The-Ear” HAs were also cheaper than “Receiver-in-Canal” HAs. Among In-Ear HAs, “In-the-Canal” and “Completely-in-Canal” were more popular than “In-the-Ear” HAs despite costing more. HA was used ≥4 days/week by 85.6% but >7 h per day by only 35.7%. Only 18% received bilateral first HA fitting. In multivariate analysis, younger age and symmetrical HL were predictors of bilateral HA uptake while better Pure-Tone-Audiometry of aided ear and >7 h of daily HA usage were predictors of successive HA fitting. <i>Conclusions</i>: HA users in Singapore were elderly and presented with advanced HL. Bilateral HA adoption and average daily use were low compared to other developed countries. Future research on understanding the suboptimal HA usage should explore patients' motivation, hearing disability, and HA effectiveness.</p