Dr. Amina Naidja, Dr. Saif Eddine Chettah, Dr. Dalal Farid, Dr. Meriem Benmachiche, Pr. Alkama Djamel
{"title":"A Comprehensive Review on Significance of Machine Learning in Medical Science","authors":"Dr. Amina Naidja, Dr. Saif Eddine Chettah, Dr. Dalal Farid, Dr. Meriem Benmachiche, Pr. Alkama Djamel","doi":"10.20431/2349-4859.0901001","DOIUrl":"https://doi.org/10.20431/2349-4859.0901001","url":null,"abstract":"","PeriodicalId":276242,"journal":{"name":"International Journal of Research Studies in Computer Science and Engineering","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131116707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Prediction of Women Obesity using Naive Baye's Algorithm","authors":"Rakshitha Kiran","doi":"10.20431/2349-4859.0602002","DOIUrl":"https://doi.org/10.20431/2349-4859.0602002","url":null,"abstract":"Obesity is a familiar problem nowadays and in women within age 19-35 can cause infertility, miscarriage, heart diseases, diabetes, hypertension, arthritis etc. Every year the percentage of obesity is increasing. Predicting obesity at an earlier stage will be helpful for people to be more cautious about their health. The data sets of women within the age 19-35 are collected from various sources. The risk factors causing obesity is considered and Naive Baye's algorithm is applied to predict the obesity. The main aim of this work is to show the society, the adverse effect of being obese and also to analyze the risk factors causing obesity. Accuracy of the Naive Baye's model is calculated and results show that the algorithm can be applied for better prediction which can be used by doctors, patients, biomedical researchers.","PeriodicalId":276242,"journal":{"name":"International Journal of Research Studies in Computer Science and Engineering","volume":"10 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124932339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Implementing and Evaluating Impact of Task Scheduling in Cloud Environment","authors":"G. Jagdev","doi":"10.20431/2349-4859.0602001","DOIUrl":"https://doi.org/10.20431/2349-4859.0602001","url":null,"abstract":"Cloud computing has found its widespread use because of the several provisions it has enabled and made easier in technology sector. The research paper is intended to analyze and implement the three prominent task scheduling algorithms (FCFS, SJF, RR) which plays critical role in cloud computing. The more efficiently the processes are organized for execution on remote servers, the more optimal gets the performance of cloud setup. The paper elaborated the performance of three task scheduling algorithms under different scenarios and an effective conclusion has been reached.","PeriodicalId":276242,"journal":{"name":"International Journal of Research Studies in Computer Science and Engineering","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117125718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Network Intrusion Detection: Comparative Analysis of NSL-KDD and CIC-IDS2017 Datasets","authors":"Ritesh Kumar, G. Jagdev","doi":"10.20431/2349-4859.0902001","DOIUrl":"https://doi.org/10.20431/2349-4859.0902001","url":null,"abstract":": The research paper explores NSL-KDD and CIC-IDS2017 datasets and implementing multiple encoding techniques on these datasets. The three categories of encoding techniques implemented on NSL-KDD dataset are One Hot Encoding, Removal of missing values, and Removal of Categorical Data. The six categories of encoding techniques implemented on CIC-IDS2017 are Eliminating categorical data or missing values, Imputing mode for missing values, Imputing median for missing values, Imputing mean for missing values, Imputing 0 for missing values, and Simple imputer. Thereafter the true labels (Binary True labels and Multiclass True labels) are implemented. The clustering is performed on the datasets using K-Means, Isolation Forest, DBSCAN, and Local Outlier Factor. For NSL-KDD, the Score Metrics Menu with three options to calculate among F1 score, Normalized Mutual Info Score, and Adjusted Rand Score using the appropriate Average Method is implemented and the score of the desired parameter is evaluated. For CIC-IDS2017, the Score Metrics Menu with three options to calculate among F1 score, Normalized Mutual Info Score, and Adjusted Rand Score using the appropriate Average Method is encountered and the score of the desired parameter is evaluated.","PeriodicalId":276242,"journal":{"name":"International Journal of Research Studies in Computer Science and Engineering","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124955107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Improved Link Prediction in Social Networks using Label Propagation","authors":"Shadi sharifpour, M. Bateni","doi":"10.20431/2349-4859.0603004","DOIUrl":"https://doi.org/10.20431/2349-4859.0603004","url":null,"abstract":"Social communications can effectively assist social networks in order to keep their active users and improve services of social networks. Therefore, they should have good prediction of social communications between their users. In this way, link prediction issue in social networks has interested many researchers and increasing prediction accuracy in social networks in under focus. There are three approaches for solving link prediction problem: similarity-based approach, an approach based on maximum likehood and probabilistic model-based approach. In this paper, similarity-based approach is utilized. Also, label propagation concept is used for link prediction and in order to raise accuracy in link prediction algorithm by using label propagation, the distance of the shortest path is applied for label propagation in network. Presented method, with AUC metric is tested on football data set, Email network, science network and power network. Total results of this test show that proposed method is improved basic method about 17.133%.","PeriodicalId":276242,"journal":{"name":"International Journal of Research Studies in Computer Science and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130978071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Examining the Usage of Flutter to Design a Yatch in 3D","authors":"Mohammed Kpannah Fahnbulleh, Xu Shuobo","doi":"10.20431/2349-4859.0801001","DOIUrl":"https://doi.org/10.20431/2349-4859.0801001","url":null,"abstract":"The purpose of this paper is to evaluate Flutter as a UI tool for creating mobile applications. A method that is used for creating mobile applications is by creating them for a specific platform from the beginning. Another method is to write a code base that can be compiled to several types of platforms. It is a method called cross-platform and is a popular method because of how flexible and fast a mobile application can be created. Choosing between native and cross-platforms is often a question about money and the proper way of developing. Flutter is an open-source UI toolkit that uses the language Dart [15] that can create mobile applications with a single code base and compile the code into both Android and iOS [11]. It was created by Google year 2018 and can according to themselves, create applications that inherits the same type of look, feel and performance as if they would have been developed as a native mobile application. This paper contains a study where Flutter is compared to native applications in different aspects such as performance of the CPU, visuals, code complexity and code needed to perform its designated task.","PeriodicalId":276242,"journal":{"name":"International Journal of Research Studies in Computer Science and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130265804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Tashtoush, Carlos Ruiz, Tiffany Estevis, Esteban Herrera, Raul Bernal, Rolando, Martinez, Luis Reyna
{"title":"Square Spiral Search (SSS) Algorithm for Cooperative Robots: Mars Exploration","authors":"T. Tashtoush, Carlos Ruiz, Tiffany Estevis, Esteban Herrera, Raul Bernal, Rolando, Martinez, Luis Reyna","doi":"10.20431/2349-4859.0701003","DOIUrl":"https://doi.org/10.20431/2349-4859.0701003","url":null,"abstract":"National Aeronautics and Space Administration (NASA) ignited a movement for the exploration of space, in collaboration with the University of New Mexico (UNM). In 2016, NASA Swarmathon was established, granting opportunities for students to test their programming proficiency competitively against colleges across the nation. The main objective of this competition is for multiple rovers to search, retrieve, and deliver resources to a designated home base autonomously simulating ant behavior.","PeriodicalId":276242,"journal":{"name":"International Journal of Research Studies in Computer Science and Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122483402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Tashtoush, R. Hernandez, Raquel Yanez, J. González, Hector Moreno, Valeria Escobar
{"title":"Reverse-Twister Swarm Search Algorithm Design: NASA Swarmathon Competition","authors":"T. Tashtoush, R. Hernandez, Raquel Yanez, J. González, Hector Moreno, Valeria Escobar","doi":"10.20431/2349-4859.0701004","DOIUrl":"https://doi.org/10.20431/2349-4859.0701004","url":null,"abstract":"To revolutionize space exploration techniques, the DustySWARM team from Texas A&M International University took the challenge to improve current search algorithms. The focus of the research was to create an efficient search algorithm applicable to the future mission of NASA space exploration. The use of autonomous search rovers that can react to their environment facilitates the exploration of unknown territories. Furthermore, swarms of autonomous robots reduce the data and resource collection period. In nature, swarms of animals and insects have developed, by instinct, searching systems to collect resources for food and shelter. Within the groups, the ability to achieve their goal of resource collection is obtained by systems of communication and reactions to the environment. Similarly, robot swarms can collaborate to explore unknown terrain. Previous search algorithms have been developed, such as the iAnt code developed by the University of New Mexico, which implements the use of sensor feedback and programmed decision logic to search for and collect resources.","PeriodicalId":276242,"journal":{"name":"International Journal of Research Studies in Computer Science and Engineering","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122440474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Execution of LEACH Intended for Curtailing Energy Consumption in Wireless Networks","authors":"Sukhpreet Kaur, Dr.Gagandeep Jagdev","doi":"10.20431/2349-4859.0801002","DOIUrl":"https://doi.org/10.20431/2349-4859.0801002","url":null,"abstract":"WSN (Wireless sensor network) is a part of WANETs (Wireless Ad hoc Networks). LEACH is a hierarchical cluster based routing protocol. LEACH is the most popular hierarchical cluster based routing protocol for a wireless sensor network. Every node makes use of a stochastic algorithm at each round to decide whether it will become a CH in the current round [1, 2]. LEACH assumes that each node has a radio powerful enough to directly reach the base station or the nearest cluster head, but making use of this radio at maximum power would be waste of energy. Nodes which have been CHs cannot become CH again for X rounds, where X refers to the desired percentage of CHs. Subsequently, each node has a probability of 1/X of becoming a CH again. At the end of each round, each node that is not a CH selects the closest CH and joins that cluster [3, 4]. The CH then come up with a schedule for each node in its cluster to transmit its data. All nodes that are not CHs only connect with the cluster head in a TDMA fashion, according to the schedule created by the CH. They do so using the minimum energy needed to reach the cluster head, and only need to keep their radios on during their time slot [5, 6, 7].","PeriodicalId":276242,"journal":{"name":"International Journal of Research Studies in Computer Science and Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129833227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exploring Influence of Big Data Analytics in Retail Sector","authors":"G. Jagdev","doi":"10.20431/2349-4859.0601001","DOIUrl":"https://doi.org/10.20431/2349-4859.0601001","url":null,"abstract":"The data today is no longer that simple as it looked few decades ago. In today’s hi-tech world, the data has completely changed it shape and size. Many organizations surviving in different sectors have opted to handle this huge amount of data for their benefits in terms of economy. Such data which is huge in size, is accumulated at very high rate and have different formats, is referred as Big Data. The need of hour is to fetch out the concealed knowledge from this enormous amount of data. The purpose of extracting knowledge is to utilize it in most effective and efficient manner [1]. There is no limit to this data. It multiplies itself exponentially each day. Several websites comes into existence each day. Millions and billions of images, photos, videos, songs, etc., are uploaded on the internet each day. This data needs to be processed and achieve two primary objectives of description and prediction. Description is intended to accomplish analysis and mining of data in order to extract the latest information according to one’s preferences. Prediciton focuses on providing answers to the upcoming questions on the basis of past records [2, 3].","PeriodicalId":276242,"journal":{"name":"International Journal of Research Studies in Computer Science and Engineering","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121405377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}