In high dimensional data, Principal Component Analysis (PCA)-based Pearson correlation remains broadly employed to reduce the data dimensions and to improve the effectiveness of the clustering partitions. Besides being prone to sensitivity on non-Gaussian distributed data, in a high dimensional data analysis, this algorithm may influence the partitions of cluster as well as generate exceptionally imbalanced clusters due to its assigned equal weight to each observation pairs. To solve the unbalanced clusters in hydrological study caused by skewed character of the dataset, this study came out with a robust method of PCA in term of the correlation. This study will explain a RPCA to be proposed as an alternative to classical PCA in reducing high dimensional dataset to a lower form as well as obtain balance clustering result. This study improved where RPCA managed to downweigh the far-from-center outliers and develop the cluster partitions. The results for both methods are compared in term .....

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Fruits have nutrients and health-promoting compounds and usually fruits are eaten fresh with minimally processed. To meet rising demand, the production and processing of horticultural crops of fruits have grown massively in response to the population and changing dietary habits. It is rarely known that some fruit wastes, including peel, actually have their own advantages to humans as well as industry. In fact, these fruit wastes, including fruit peel, should be handled and used to minimise the environmental impacts. The functional properties of the peel of banana, pomegranate, papaya, and citrus fruits such as lemon and orange can beneficially help in the production of new health products and in food industries. Antimicrobial compounds in fruit peel play an important role in inhibiting the microbial growth, specifically pathogenic microorganisms such as Escherichia coli, Bacillus aureus, Campylobacter, Salmonella, and Staphylococcus aureus. The antimicrobial compounds present in the fr.....

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Silver nanoparticles (AgNP) have been used in many medical and biological applications due to their unique features and characteristics. One of the most important issues researchers address in nanoscience is finding suitable methods to produce nanoparticles with environmentally friendly and non-toxic properties. The unique chemical, physical and biological properties that AgNP possesses give that impetus to developing their production methods. In recent years, there have been many studies documented for the production of AgNP during the development of green synthesis methods (GSM). The present study describes methods for the GSM of AgNP, their biological properties, and other applications, giving the most appropriate methods to synthesize AgNP.AgNP is one of the essential metallic particles, as they can be manufactured and designed in easy ways, and they are also adjustable because they were used in many fields such as catalysts, ideal biometrics, and photo-controlled delivery Systems......

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This study utilized a literature review strategy to examine prior literature pertaining to the frameworks concerning how to minimize users? pain and maximize their pleasure while interacting with the designs of interactive products. The findings of the study reveal that several such frameworks are in existence and are mainly in other domains different from usability and user experience. In these, the emphasis were mostly on satisfaction and dissatisfaction criteria which do not cover the broader perspectives of user experience that comprise hedonic, affective, aesthetics and other hedonomic facets. This prompts for the development of a framework that tailored to usability and user experience concerns to enable user experience designers design interactive products that will enhance users? experience. The proposed framework was adapted from previous related frameworks It is a three-factor framework that is composed of pain factors, linear factors and pleasure factors. The study proposes .....

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This work proposes a pattern recognition model for static gestures in Malaysian Sign Language (MSL) based on Machine Learning (ML) techniques. The proposed model is divided into two phases, namely, data acquisition and data processing. The first phase involves capturing the required sign data, such as the shape and orientation of the hand, to construct a sensor-based SL dataset. The dataset is collected using a DataGlove device. This device is used to measure the motions of the fingers and wrists. Sixty-four features represent each sign in the dataset. The collected sensory dataset is cleaned in the second phase by removing redundant data. Then, the features are scaled and normalised to exhibit symmetrical behaviour and eliminate outliers. Then, ten different ML techniques are utilised based on real-time data for SL gesture recognition. Experimental results confirmed the efficacy of the proposed pattern recognition model compared with previous work. ? 2021..

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A phytochemical investigation of the stem bark of Calophyllum canum resulted in the isolation of a new xanthone dimer identified as biscaloxanthone (1), together with four compounds; trapezifoliaxanthone (2), trapezifolixanthone A (3), taraxerone (4) and taraxerol (5). The structures of these compounds were determined via spectroscopic methods of IR, UV, MS and NMR (1D and 2D). The cytotoxicity of compounds 1-3 were screened against A549, MCF-7, C33A and 3T3L1 cell lines, wherein weak cytotoxic activities were observed (IC50 > 50 ?m). 2020 Walter de Gruyter GmbH, Berlin/Boston 2020...

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Given the rapid development of dehazing image algorithms, selecting the optimal algorithm based on multiple criteria is crucial in determining the efficiency of an algorithm. However, a sufficient number of criteria must be considered when selecting an algorithm in multiple foggy scenes, including inhomogeneous, homogenous and dark foggy scenes. However, the selection of an optimal real-time image dehazing algorithm based on standardised criteria presents a challenge. According to previous studies, a standardisation and selection framework for real-time image dehazing algorithms based on multi-foggy scenes is not yet available. To address this gap, this study proposes a new standardisation and selection framework based on fuzzy Delphi (FDM) and hybrid multi-criteria analysis methods. Experiments are also conducted in three phases. Firstly, the image dehazing criteria are standardised based on FDM. Secondly, an evaluation experiment is conducted based on standardised criteria and nine r.....

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This paper introduces the concept of triangular citation that combines direct citation, co-citation and bibliographic coupling, and defines three kinds of literature used in triangular citation, namely, original Literature A, intermediary Literature B and following Literature C. Taking citation data from the CNKI database as the experimental sample, it was found that there are triangular citations in the actual citation network, with a high coverage rate. Additionally, the authors analyzed the triangular citation sample data from the different perspectives of reference time, literature type, impact factor, interdisciplinary citation, and the author's self-citation, thereby finding the external characteristics of literature and internal trends of citation in the triangular citation. Additionally, it was concluded that the literature between A and C has an "indirect citation"mechanism. The citation characteristics of the two, i.e., A and C, are different from the direct citation relation.....

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Driver behavior is a concerning issue in the area of intelligent transportation system (ITS). Driver behavior is a significant key player in a wide range of unpleasant events during the ride, such as accidents or crashes, traffic congestion, harsh braking, and acceleration/deceleration. Influencing factors of driver behavior have been explored in several studies. It is imperative to investigate these factors in order to provide a comprehensive analysis and to categorize them on the basis of a coherent taxonomy. With that, this study conducted a systematic review on prior studies that focused on bus driver behavior, particularly in the ITS. This study also established a taxonomy on the topic of driver behavior in multiple areas of ITS and their classifications. Different databases, namely ScienceDirect, Web of Science, and IEEE Explore, were utilized to obtain relevant articles from 2008 to 2021 (15 April). Several filtering and scanning stages were performed according to the exclusion/.....

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The Logistic Regression Model (LRM) is successful in many fields due to its capability of predicting and describing the relationship between binary response variables and one or more independent variables. However, the prediction results of this model are still not accurate enough due to error terms, regardless of their existence in the model. To overcome this problem and, at the same time, produce more accurate and efficient predictive model values, the bootstrap approach was proposed. Unfortunately, this approach did not receive any attention, especially for this model. This study aims to introduce the bootstrap approach to LRM and investigate the performance of the proposed models using data on wound healing using jellyfish collagen. The results revealed that the proposed model generated smaller values of MSE and RMSE, as well as shorter confidence intervals, compared with the existing LRM. These results proved that the proposed model could produce an estimated value that is more ac.....

779 hits