Pub Date : 2018-06-01DOI: 10.1016/j.fcij.2017.11.002
Heba Hamdy Ali , Hossam M. Moftah , Aliaa A.A. Youssif
Depth Maps-based Human Activity Recognition is the process of categorizing depth sequences with a particular activity. In this problem, some applications represent robust solutions in domains such as surveillance system, computer vision applications, and video retrieval systems. The task is challenging due to variations inside one class and distinguishes between activities of various classes and video recording settings. In this study, we introduce a detailed study of current advances in the depth maps-based image representations and feature extraction process. Moreover, we discuss the state of art datasets and subsequent classification procedure. Also, a comparative study of some of the more popular depth-map approaches has provided in greater detail. The proposed methods are evaluated on three depth-based datasets “MSR Action 3D”, “MSR Hand Gesture”, and “MSR Daily Activity 3D”. Experimental results achieved 100%, 95.83%, and 96.55% respectively. While combining depth and color features on “RGBD-HuDaAct” Dataset, achieved 89.1%.
基于深度图的人类活动识别是对具有特定活动的深度序列进行分类的过程。在这个问题中,一些应用程序在诸如监视系统、计算机视觉应用程序和视频检索系统等领域中代表了健壮的解决方案。由于一个班级内部的变化,以及不同班级的活动和视频录制设置的区别,这项任务具有挑战性。在本研究中,我们详细介绍了目前基于深度图的图像表示和特征提取过程的研究进展。此外,我们还讨论了最新的数据集和随后的分类过程。此外,对一些更流行的深度图方法的比较研究提供了更详细的信息。在三个基于深度的数据集“MSR Action 3D”、“MSR Hand Gesture”和“MSR Daily Activity 3D”上对所提出的方法进行了评估。实验结果分别达到100%、95.83%和96.55%。在“RGBD-HuDaAct”数据集上结合深度和颜色特征,达到89.1%。
{"title":"Depth-based human activity recognition: A comparative perspective study on feature extraction","authors":"Heba Hamdy Ali , Hossam M. Moftah , Aliaa A.A. Youssif","doi":"10.1016/j.fcij.2017.11.002","DOIUrl":"10.1016/j.fcij.2017.11.002","url":null,"abstract":"<div><p>Depth Maps-based Human Activity Recognition is the process of categorizing depth sequences with a particular activity. In this problem, some applications represent robust solutions in domains such as surveillance system, computer vision applications, and video retrieval systems. The task is challenging due to variations inside one class and distinguishes between activities of various classes and video recording settings. In this study, we introduce a detailed study of current advances in the depth maps-based image representations and feature extraction process. Moreover, we discuss the state of art datasets and subsequent classification procedure. Also, a comparative study of some of the more popular depth-map approaches has provided in greater detail. The proposed methods are evaluated on three depth-based datasets “MSR Action 3D”, “MSR Hand Gesture”, and “MSR Daily Activity 3D”. Experimental results achieved 100%, 95.83%, and 96.55% respectively. While combining depth and color features on “RGBD-HuDaAct” Dataset, achieved 89.1%.</p></div>","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"3 1","pages":"Pages 51-67"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.fcij.2017.11.002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84946919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1016/j.fcij.2017.10.007
Ola M. El Zein , Lamiaa M. El Bakrawy , Neveen I. Ghali
A new robust 3D watermarking algorithm utilizing Fuzzy C-Means (FCM) clustering technique is presented. FCM clusters 3D mesh vertices into suitable and unsuitable choices to insert the watermark without occasioning visible deformation, and also it is tough for the attacker to determine places of the watermark insertion. Two watermarking processes are offered to insert the watermark into 3D mesh models. The first process utilizes topical statistical measurements like average and standard deviation in order to alter the values of vertices to secret watermark data into 3D mesh models, however, the second process utilizes a jumbled insertion planning to insert the watermark inside 3D mesh models utilizing the topical statistical measurements and altering 3D mesh vertices together. Simulation results show that the proposed algorithm is robust. The watermarked 3D mesh models are resistant to several attacks like similarity transforms, noise addition, cropping and mesh smoothing.
{"title":"A robust 3D mesh watermarking algorithm utilizing fuzzy C-Means clustering","authors":"Ola M. El Zein , Lamiaa M. El Bakrawy , Neveen I. Ghali","doi":"10.1016/j.fcij.2017.10.007","DOIUrl":"10.1016/j.fcij.2017.10.007","url":null,"abstract":"<div><p>A new robust 3D watermarking algorithm utilizing Fuzzy C-Means (FCM) clustering technique is presented. FCM clusters 3D mesh vertices into suitable and unsuitable choices to insert the watermark without occasioning visible deformation, and also it is tough for the attacker to determine places of the watermark insertion. Two watermarking processes are offered to insert the watermark into 3D mesh models. The first process utilizes topical statistical measurements like average and standard deviation in order to alter the values of vertices to secret watermark data into 3D mesh models, however, the second process utilizes a jumbled insertion planning to insert the watermark inside 3D mesh models utilizing the topical statistical measurements and altering 3D mesh vertices together. Simulation results show that the proposed algorithm is robust. The watermarked 3D mesh models are resistant to several attacks like similarity transforms, noise addition, cropping and mesh smoothing.</p></div>","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"2 2","pages":"Pages 148-156"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.fcij.2017.10.007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86210599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1016/j.fcij.2017.10.001
Jyotiprava Dash, Nilamani Bhoi
Retinal imaging has become the significant tool among all the medical imaging technology, due to its capability to extract many data which is linked to various eye diseases. So, the accurate extraction of blood vessel is necessary that helps the eye care specialists and ophthalmologist to identify the diseases at the early stages. In this paper, we have proposed a computerized technique for extraction of blood vessels from fundus images. The process is conducted in three phases: (i) pre-processing where the image is enhanced using contrast limited adaptive histogram equalization and median filter, (ii) segmentation using mean-C thresholding to extract retinal blood vessels, (iii) post-processing where morphological cleaning operation is used to remove isolated pixels. The performance of the proposed method is tested on and experimental results show that our method achieve an accuracies of 0.955 and 0.954 on Digital retinal images for vessel extraction (DRIVE) and Child heart and health study in England (CHASE_DB1) databases respectively.
{"title":"A thresholding based technique to extract retinal blood vessels from fundus images","authors":"Jyotiprava Dash, Nilamani Bhoi","doi":"10.1016/j.fcij.2017.10.001","DOIUrl":"10.1016/j.fcij.2017.10.001","url":null,"abstract":"<div><p>Retinal imaging has become the significant tool among all the medical imaging technology, due to its capability to extract many data which is linked to various eye diseases. So, the accurate extraction of blood vessel is necessary that helps the eye care specialists and ophthalmologist to identify the diseases at the early stages. In this paper, we have proposed a computerized technique for extraction of blood vessels from fundus images. The process is conducted in three phases: (i) pre-processing where the image is enhanced using contrast limited adaptive histogram equalization and median filter, (ii) segmentation using mean-C thresholding to extract retinal blood vessels, (iii) post-processing where morphological cleaning operation is used to remove isolated pixels. The performance of the proposed method is tested on and experimental results show that our method achieve an accuracies of 0.955 and 0.954 on Digital retinal images for vessel extraction (DRIVE) and Child heart and health study in England (CHASE_DB1) databases respectively.</p></div>","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"2 2","pages":"Pages 103-109"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.fcij.2017.10.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73757787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1016/j.fcij.2017.07.004
Abhishek Bhola, Shafa Mahajan, Shailendra Singh
Gene expression dataset derived from microarray experiments are marked by large number of genes, which contains the gene expression values at different sample conditions/time-points. Selection of informative genes from these large datasets is an issue of major concern for various researchers and biologists. In this study, we propose a gene selection and dimensionality reduction method called Adaptive Analytic Hierarchy Process (A2HP). Traditional analytic hierarchy process is a multiple-criteria based decision analysis method whose result depends upon the expert knowledge or decision makers. It is mainly used to solve the decision problems in different fields. On the other hand, A2HP is a fused method that combines the outcomes of five individual gene selection ranking methods t-test, chi-square variance test, z-test, wilcoxon test and signal-to-noise ratio (SNR). At first, the preprocessing of gene expression dataset is done and then the reduced number of genes obtained, will be fed as input for A2HP. A2HP utilizes both quantitative and qualitative factors to select the informative genes. Results demonstrate that A2HP selects efficient number of genes as compared to the individual gene selection methods. The percentage of deduction in number of genes and time complexity are taken as the performance measure for the proposed method. And it is shown that A2HP outperforms individual gene selection methods.
{"title":"Informative gene selection using Adaptive Analytic Hierarchy Process (A2HP)","authors":"Abhishek Bhola, Shafa Mahajan, Shailendra Singh","doi":"10.1016/j.fcij.2017.07.004","DOIUrl":"10.1016/j.fcij.2017.07.004","url":null,"abstract":"<div><p>Gene expression dataset derived from microarray experiments are marked by large number of genes, which contains the gene expression values at different sample conditions/time-points. Selection of informative genes from these large datasets is an issue of major concern for various researchers and biologists. In this study, we propose a gene selection and dimensionality reduction method called Adaptive Analytic Hierarchy Process (A2HP). Traditional analytic hierarchy process is a multiple-criteria based decision analysis method whose result depends upon the expert knowledge or decision makers. It is mainly used to solve the decision problems in different fields. On the other hand, A2HP is a fused method that combines the outcomes of five individual gene selection ranking methods t-test, chi-square variance test, z-test, wilcoxon test and signal-to-noise ratio (SNR). At first, the preprocessing of gene expression dataset is done and then the reduced number of genes obtained, will be fed as input for A2HP. A2HP utilizes both quantitative and qualitative factors to select the informative genes. Results demonstrate that A2HP selects efficient number of genes as compared to the individual gene selection methods. The percentage of deduction in number of genes and time complexity are taken as the performance measure for the proposed method. And it is shown that A2HP outperforms individual gene selection methods.</p></div>","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"2 2","pages":"Pages 94-102"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.fcij.2017.07.004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91414392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1016/j.fcij.2017.10.003
P. Dhanalakshmi , K. Ramani , B. Eswara Reddy
Applying machine learning techniques to on-line biomedical databases is a challenging task, as this data is collected from large number of sources and it is multi-dimensional. Also retrieval of relevant document from large repository such as gene document takes more processing time and an increased false positive rate. Generally, the extraction of biomedical document is based on the stream of prior observations of gene parameters taken at different time periods. Traditional web usage models such as Markov, Bayesian and Clustering models are sensitive to analyze the user navigation patterns and session identification in online biomedical database. Moreover, most of the document ranking models on biomedical database are sensitive to sparsity and outliers. In this paper, a novel user recommendation system was implemented to predict the top ranked biomedical documents using the disease type, gene entities and user navigation patterns. In this recommendation system, dynamic session identification, dynamic user identification and document ranking techniques were used to extract the highly relevant disease documents on the online PubMed repository. To verify the performance of the proposed model, the true positive rate and runtime of the model was compared with that of traditional static models such as Bayesian and Fuzzy rank. Experimental results show that the performance of the proposed ranking model is better than the traditional models.
{"title":"An improved rank based disease prediction using web navigation patterns on bio-medical databases","authors":"P. Dhanalakshmi , K. Ramani , B. Eswara Reddy","doi":"10.1016/j.fcij.2017.10.003","DOIUrl":"10.1016/j.fcij.2017.10.003","url":null,"abstract":"<div><p>Applying machine learning techniques to on-line biomedical databases is a challenging task, as this data is collected from large number of sources and it is multi-dimensional. Also retrieval of relevant document from large repository such as gene document takes more processing time and an increased false positive rate. Generally, the extraction of biomedical document is based on the stream of prior observations of gene parameters taken at different time periods. Traditional web usage models such as Markov, Bayesian and Clustering models are sensitive to analyze the user navigation patterns and session identification in online biomedical database. Moreover, most of the document ranking models on biomedical database are sensitive to sparsity and outliers. In this paper, a novel user recommendation system was implemented to predict the top ranked biomedical documents using the disease type, gene entities and user navigation patterns. In this recommendation system, dynamic session identification, dynamic user identification and document ranking techniques were used to extract the highly relevant disease documents on the online PubMed repository. To verify the performance of the proposed model, the true positive rate and runtime of the model was compared with that of traditional static models such as Bayesian and Fuzzy rank. Experimental results show that the performance of the proposed ranking model is better than the traditional models.</p></div>","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"2 2","pages":"Pages 133-147"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.fcij.2017.10.003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83678070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1016/j.fcij.2017.07.002
Raviajot Kaur, Abhishek Bhola, Shailendra Singh
Genes of an organism play a very crucial role in the working of various cellular activities. Genes and other biological molecules like DNA, RNA do not operate alone but they all are correlated. Their relationships are shown with the help of networks commonly known as Gene Regulatory Networks. Gene Regulatory Networks are complex control networks that show the map of interactions among the genes. They provide very useful contribution to the genomic science and increase the understanding of various biological processes. In this paper, fuzzy logic based method is proposed for the reverse engineering of gene regulatory network from microarray gene expression datasets. Pre-processing steps have been introduced to increase the efficiency of the method. Clustering technique is also employed to divide the problem into sub problems to reduce the computational complexity at some extent. Finally, the proposed method is tested on two different time course gene expression datasets of yeast having GEO accession number GDS37 and GDS3030. The results are validated by using Specificity, Sensitivity and F-score as parameters. Results of the proposed method are further compared with other existing method which was proposed by Al-Shobaili in 2014.
{"title":"A novel fuzzy logic based reverse engineering of gene regulatory network","authors":"Raviajot Kaur, Abhishek Bhola, Shailendra Singh","doi":"10.1016/j.fcij.2017.07.002","DOIUrl":"10.1016/j.fcij.2017.07.002","url":null,"abstract":"<div><p>Genes of an organism play a very crucial role in the working of various cellular activities. Genes and other biological molecules like DNA, RNA do not operate alone but they all are correlated. Their relationships are shown with the help of networks commonly known as Gene Regulatory Networks. Gene Regulatory Networks are complex control networks that show the map of interactions among the genes. They provide very useful contribution to the genomic science and increase the understanding of various biological processes. In this paper, fuzzy logic based method is proposed for the reverse engineering of gene regulatory network from microarray gene expression datasets. Pre-processing steps have been introduced to increase the efficiency of the method. Clustering technique is also employed to divide the problem into sub problems to reduce the computational complexity at some extent. Finally, the proposed method is tested on two different time course gene expression datasets of yeast having GEO accession number GDS37 and GDS3030. The results are validated by using Specificity, Sensitivity and F-score as parameters. Results of the proposed method are further compared with other existing method which was proposed by Al-Shobaili in 2014.</p></div>","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"2 2","pages":"Pages 79-86"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.fcij.2017.07.002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75932586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1016/j.fcij.2017.10.005
Priyadarsan Parida, Nilamani Bhoi
Transition region based approaches are recent hybrid segmentation techniques well known for its simplicity and effectiveness. Here, the segmentation effectiveness depends on robust extraction of transition regions. So, we have proposed a transition region method which initially decomposes the gray image in wavelet domain. Two existing transition region approaches are applied on approximate coefficients to extract transition region feature matrix. Using this feature matrix the corresponding prominent wavelet coefficients of different bands are found. Inverse wavelet transform are then applied on the modified coefficients to get edge image with more than one pixel width. Otsu thresholding is applied on it to get transition regions. Further, morphological operations are applied to extract the object regions. Finally, the objects are extracted using the object regions. The wavelet domain approach extracts robust transition regions resulting in better segmentation. The proposed method is compared with different existing image segmentation methods. Experimental results reveal that the proposed method achieve 0.95 overall segmentation accuracy. It also works well for extraction of single as well as multiple objects from images.
{"title":"Wavelet based transition region extraction for image segmentation","authors":"Priyadarsan Parida, Nilamani Bhoi","doi":"10.1016/j.fcij.2017.10.005","DOIUrl":"10.1016/j.fcij.2017.10.005","url":null,"abstract":"<div><p>Transition region based approaches are recent hybrid segmentation techniques well known for its simplicity and effectiveness. Here, the segmentation effectiveness depends on robust extraction of transition regions. So, we have proposed a transition region method which initially decomposes the gray image in wavelet domain. Two existing transition region approaches are applied on approximate coefficients to extract transition region feature matrix. Using this feature matrix the corresponding prominent wavelet coefficients of different bands are found. Inverse wavelet transform are then applied on the modified coefficients to get edge image with more than one pixel width. Otsu thresholding is applied on it to get transition regions. Further, morphological operations are applied to extract the object regions. Finally, the objects are extracted using the object regions. The wavelet domain approach extracts robust transition regions resulting in better segmentation. The proposed method is compared with different existing image segmentation methods. Experimental results reveal that the proposed method achieve 0.95 overall segmentation accuracy. It also works well for extraction of single as well as multiple objects from images.</p></div>","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"2 2","pages":"Pages 65-78"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.fcij.2017.10.005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89386267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1016/j.fcij.2017.09.002
D.R. Kumar Raja, S. Pushpa
It is widely acknowledged today that E-Commerce business is growing rapidly. This is happened only because of people are completely depending on the ratings and reviews given by the customers who are already purchased and using the products. Online surveys, customer reviews on shopping sites are the key sources to understand customer requirements and feedback to help upgrade the product quality and achieve greater outcomes. Now the challenge is that whether those reviews came from product level or feature level will be the million dollar question. To overcome this problem we are proposing a new algorithm to give feature level rating for the product which is called Feature Level Review Rating Analysis (FLRRA) algorithm.
{"title":"Feature level review table generation for E-Commerce websites to produce qualitative rating of the products","authors":"D.R. Kumar Raja, S. Pushpa","doi":"10.1016/j.fcij.2017.09.002","DOIUrl":"10.1016/j.fcij.2017.09.002","url":null,"abstract":"<div><p>It is widely acknowledged today that E-Commerce business is growing rapidly. This is happened only because of people are completely depending on the ratings and reviews given by the customers who are already purchased and using the products. Online surveys, customer reviews on shopping sites are the key sources to understand customer requirements and feedback to help upgrade the product quality and achieve greater outcomes. Now the challenge is that whether those reviews came from product level or feature level will be the million dollar question. To overcome this problem we are proposing a new algorithm to give feature level rating for the product which is called Feature Level Review Rating Analysis (FLRRA) algorithm.</p></div>","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"2 2","pages":"Pages 118-124"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.fcij.2017.09.002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75149652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1016/j.fcij.2017.09.001
Sankar Prasad Mondal, Manimohan Mandal
The paper presents an adaptation of pentagonal fuzzy number. Different type of pentagonal fuzzy number is formed. The arithmetic operation of a particular type of pentagonal fuzzy number is addressed here. The difference between two pentagonal valued functions is also addressed here. Demonstration of pentagonal fuzzy solutions of fuzzy equation is carried out with the said numbers. Additionally, an illustrative example is also taken with the useful graph and table for usefulness for attained to the proposed concept.
{"title":"Pentagonal fuzzy number, its properties and application in fuzzy equation","authors":"Sankar Prasad Mondal, Manimohan Mandal","doi":"10.1016/j.fcij.2017.09.001","DOIUrl":"10.1016/j.fcij.2017.09.001","url":null,"abstract":"<div><p>The paper presents an adaptation of pentagonal fuzzy number. Different type of pentagonal fuzzy number is formed. The arithmetic operation of a particular type of pentagonal fuzzy number is addressed here. The difference between two pentagonal valued functions is also addressed here. Demonstration of pentagonal fuzzy solutions of fuzzy equation is carried out with the said numbers. Additionally, an illustrative example is also taken with the useful graph and table for usefulness for attained to the proposed concept.</p></div>","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"2 2","pages":"Pages 110-117"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.fcij.2017.09.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82414787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1016/j.fcij.2017.10.002
V. Bassoo , V. Hurbungs , V. Ramnarain-Seetohul , T.P. Fowdur , Y. Beeharry
According to the National Transport Authority (NTA), there were 493,081 registered vehicles in Mauritius in April 2016, which represents a 1.4% annual increase compared to 2015. Despite the sensitization campaigns and the series of measures setup by the Minister of Public Infrastructure and Land Transport, the number of road accidents continues to rise. The three main elements that contribute to accidents are: road infrastructure, vehicle and driver. The driver has the highest contribution in collisions. If the driver is given the right information (e.g. driving behaviour, accident-prone areas and vehicle status) at the right time, he/she can make better driving decisions and react promptly to critical situations. This paper proposes a framework for safer driving in Mauritius that uses an on-board car diagnostic module (OBDII) to collect data such as vehicle average speed, engine revolution and acceleration. This module relays the data to a cloud environment where an adaptive algorithm analyses the data and predicts driver behaviour in real-time. Based on driving behaviour, mobile alerts can be sent to the driver in the form of messages, voice commands or beeps. A survey was also carried out to evaluate the acceptance rate of such a framework by people of different age groups in Mauritius.
{"title":"A framework for safer driving in Mauritius","authors":"V. Bassoo , V. Hurbungs , V. Ramnarain-Seetohul , T.P. Fowdur , Y. Beeharry","doi":"10.1016/j.fcij.2017.10.002","DOIUrl":"10.1016/j.fcij.2017.10.002","url":null,"abstract":"<div><p>According to the National Transport Authority (NTA), there were 493,081 registered vehicles in Mauritius in April 2016, which represents a 1.4% annual increase compared to 2015. Despite the sensitization campaigns and the series of measures setup by the Minister of Public Infrastructure and Land Transport, the number of road accidents continues to rise. The three main elements that contribute to accidents are: road infrastructure, vehicle and driver. The driver has the highest contribution in collisions. If the driver is given the right information (e.g. driving behaviour, accident-prone areas and vehicle status) at the right time, he/she can make better driving decisions and react promptly to critical situations. This paper proposes a framework for safer driving in Mauritius that uses an on-board car diagnostic module (OBDII) to collect data such as vehicle average speed, engine revolution and acceleration. This module relays the data to a cloud environment where an adaptive algorithm analyses the data and predicts driver behaviour in real-time. Based on driving behaviour, mobile alerts can be sent to the driver in the form of messages, voice commands or beeps. A survey was also carried out to evaluate the acceptance rate of such a framework by people of different age groups in Mauritius.</p></div>","PeriodicalId":100561,"journal":{"name":"Future Computing and Informatics Journal","volume":"2 2","pages":"Pages 125-132"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.fcij.2017.10.002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79786989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}