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检索条件"丛书名=Information Systems Engineering and Management"

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Review on Skyline Query Processing Techniques over Data Stream 7

Review on Skyline Query Processing Techniques over Data Stre...

引用

7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Dzolkhifli, Zarina Ibrahim, Hamidah Hafiz Bin Mohd Hassin, Mohd Universiti Malaysia Pahang Fakulti Komputeran Pahang Malaysia Universiti Putra Malaysia Fakulti Sains Komputer Dan Teknologi Maklumat Selangor Malaysia

ISBN: (纸本)9781665414074

Data stream management has received considerable attention lately, due to continuous sources of collection and devices and is delivered in a different variety of formats to be process within small period of time. Interesting objects will be extract from the continuous data stream by processing the skyline query. However, skyline query processing over data stream poses inherent challenges and demands and require non- traditional techniques. This paper reviews the aims and challenge of skyline approaches that are relevant for data stream. Moreover, studies on the types of queries, type of data and type of sliding window were presented. Finally, an interesting research topic over data stream that have not yet been explored is identified. © 2021 IEEE.

关键词： Query processing

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Application of Internet of Things for Early Detection of COVID-19 using Wearables 7

Application of Internet of Things for Early Detection of COV...

引用

7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Uddin, Taki Borhan Uddin, Md. Muzahidul Islam, A.K.M. Islam, Salekul Shatabda, Swakkhar United International University Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665414074

As the latest pandemic spreads, the world's governing bodies have been forced to impose strict social distancing measures. This has impacted businesses and manufacturing industries worldwide, including Bangladesh's RMG sector. To aid in the rapid spread of this infectious disease, this paper illustrates a simulation of an IoT system centered on wristbands specifically designed to detect early symptoms of COVID-19 (SARS-CoV-2). The system, which includes a facemask detection system and a thermal camera, identifies potential employees who may be at risk of contracting the COVID-19 virus. We simulated the wristband system using a simulation software in order to conduct a few test cases to ensure its feasibility. The wristbands' results were largely consistent with expectations, demonstrating their ability to monitor a wearer's vitals throughout the day. When combined with an attendance system and a face mask detection system, the wristband system enables a workplace to track its employees and detect possible infected workers. © 2021 IEEE.

关键词： COVID-19

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The Abstract of Thesis Classifier by Using Naive Bayes Method 7

The Abstract of Thesis Classifier by Using Naive Bayes Metho...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Hairani, Hairani Anggrawan, Anthony Wathan, Ahmad Islahul Latif, Kumiadin Abd Marzuki, Khairan Zulfikri, Muhammad Universitas Bumigora Faculty of Engineering and Design Mataram Indonesia

ISBN: (纸本)9781665414074

The thesis is a requirement for graduation from Bumigora university. The final year student's problem is determining the research topic because the undergraduate thesis collection of Computer Science is not grouped or classified based on student competencies. The purpose of this study was to compare the performance of the naïve Bayes method with TF-IDF weighting and without TF-IDF weighting for the classification of thesis topics based on the abstract. The stages of this research are data collection, text pre-processing, term weighting with TF-IDF and without TF-IDF, Naïve Bayes method implementation, and result evaluation. Based on the results of the tests that have been done, the naïve Bayes method with TF-IDF has an accuracy of 81.74%, a precision of 86.1%, and a sensitivity of 80.15%. While the naïve Bayes method without TF-IDF weighting produces 88.69% accuracy, 89.76% precision, and 90.49% sensitivity. Thus, the naïve Bayes method without TF-IDF weighting has better performance than TF-IDF weighting for the classification of thesis topics based on the abstract. © 2021 IEEE.

关键词： Students

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Region-Based Distance Analysis of Keyphrases: A New Unsupervised Method for Extracting Keyphrases Feature from Articles 7

Region-Based Distance Analysis of Keyphrases: A New Unsuperv...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Miah, Mohammad Badrul Alam Awang, Suryanti Azad, Md. Saiful Universiti Malaysia Pahang Faculty of Computing Pekan Malaysia Pekan Malaysia Dhaka Bangladesh

ISBN: (纸本)9781665414074

Due to the exponential growth of information's and web sources, Automatic keyphrase extraction is still a challenging issue in the current research area. Keyphrases are very helpful for several tasks in natural language processing (NLP) and information retrieval (IR) systems. Feature extractions for those keyphrases execute a vital role in extracting the top-quality keyphrases and summarising the documents at a superior level. This paper proposes a new region-based distance analysis of keyphrases (RDAK) unsupervised technique for feature extraction of keyphrases from articles. The proposed method comprises six phases: data acquisition and preprocessing, data processing, distance calculation, average distance, curve plotting, and curve fitting. At first, the system inputs the collected different datasets to the preprocessing step by employing some text preprocessing techniques. Afterwards, the preprocessed data is applied to the data processing phase, and then after distance calculation, it is passed to the region-based average calculation process, then curve plotting analysis, and afterwards, the curve fitting technique is utilized. Finally, the proposed system has tested and evaluated the performance through implementing them on benchmark datasets. The proposed system will significantly improve the performance of existing keyphrase extraction techniques. © 2021 IEEE.

关键词： Feature extraction

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Bangladesh Crime Reports Analysis and Prediction 7

Bangladesh Crime Reports Analysis and Prediction

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Pavel Rahman, Md Ifranul Hoque, A. K. M Faysal Ahmed, Md. Iftekhirul, Iftekhirul Alam, Ashraful Hossain, Nahid United International University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665414074

The systematic method of detecting crime, evaluating crime patterns, and anticipating crime trends is known as crime analysis and prediction. Crime is inherently unexpected and causes societal disruption. As Bangladesh's population grows, so does the prevalence of crime, which is wreaking havoc on our society in various ways. As a result, analyzing crime data has become crucial for a better understanding of future crime patterns. Machine learning and data mining techniques can be quite useful in predicting future crime trends and patterns in this situation. Various machine learning algorithms are utilized in this study to predict future crime patterns in Bangladesh. The crime statistics are gathered from the Bangladesh Police website to analyse and predict dacoity, robbery, murder, women and child repression, kidnapping, burglary, theft, and other crimes in Bangladesh's various regions. Another dataset from ACLED has been used to predict different kinds of events such as battles, explosions, protests, riots, strategic developments, violence against civilians with geolocations of the events. This research might assist Bangladesh police and law enforcement authorities to predict, prevent, and solve future crimes. The performance and success rate of the project are highly satisfactory. All resources of the project can be found at https://***/297yykmu © 2021 IEEE.

关键词： Forecasting

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Topic Modelling and Clustering of Disaster-Related Tweets using Bilingual Latent Dirichlet Allocation and Incremental Clustering Algorithm with Support Vector Machines for Need Assessment 7

Topic Modelling and Clustering of Disaster-Related Tweets us...

引用

7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Guerzo, Lady Angelica Buen Kilkenny, Hans Aaron O. Osorio, Raphael Noel D. Villegas, Andrei Hart E. Ponay, Charmaine S. University of Santo Tomas Computer Science Manila Philippines

ISBN: (纸本)9781665414074

The occurrence of various types of disasters are thoroughly described in social media websites like Twitter which can be a useful source of data. This research aimed to solve the problem of bilinguality of data which caused a complexity that yielded inaccurate results during clustering. The researchers were able to develop a system which adds a bilingual topic model, Bilingual Latent Dirichlet, to an existing system. This research was able to compare in terms of precision, recall, accuracy, and area under the curve metrics, the clustering accuracy of the incremental clustering module with and without the bilingual topic model, while also classifying the needs that the Tweet will require. © 2021 IEEE.

关键词： Disasters

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Neural Network as a Preferred Method for Microarray Data Classification 7

Neural Network as a Preferred Method for Microarray Data Cla...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Ramadhani, Putri Tsatsabila Nasution, Benny Benyamin University of North Sumatera Faculty of Computer Science and Information Technology Medan Indonesia

ISBN: (纸本)9781665414074

According to a WHO on World Cancer Report published in February 2020, one of six cancer survior died each year. The cancer can be known and detected early have possibilty to get better treatment, so do minimized death rates affected by cancer. A person can be detected with cancer by performing an accurate analysis and classsiflcation of microarray data. Several methods and algorithms have been used in various related studies, one of them is Neural Network. In this paper, presents recent works proposing Neural Network models as classifier for cancer predection purposes used gene expression datasets to know how capable Neural Network is in classifying microarray data. © 2021 IEEE.

关键词： Classification (of information)

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IoT Based Sport Healthcare Monitoring System 7

IoT Based Sport Healthcare Monitoring System

引用

7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Samsuddin, Muhammad Naim Mohd Raffei, Anis Farihan Mat Rahman, Nur Shamsiah Abdul Universiti Malaysia Multimedia Computing Computer Vision Faculty of Computing College of Computing and Applied Sciences Pahang26600 Malaysia

ISBN: (纸本)9781665414074

The Internet of Things is considered now as one of the feasible solutions for any remote value tracking especially in the field of health monitoring. Monitoring the athlete in aspect of fitness and training progress performances are very important to avoid accident happened during training. The proposed system developed the IoT based sport healthcare monitoring system using Arduino and several sensors. A fuzzy logic algorithm is also developed to provide decision for the athlete health condition. A web-based application is also developed to allow the instructor to store and retrieve the athlete information as well as monitor the fitness training performance of the athlete. © 2021 IEEE.

关键词： Internet of things

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An Investigation of Mobile Pet Location Tracking System (PLTS) Success 7

An Investigation of Mobile Pet Location Tracking System (PLT...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Khor, Tsu Ming Phan, Koo Yuen Teoh, Ai Ping Yeck, Yin Ping Lim, Ean Heng Wong, Pei Voon Universiti Tunku Abdul Rahman Department of Computer Science Kampar Malaysia Universiti Sains Malaysia Graduate School of Business Penang Malaysia Universiti Tunku Abdul Rahman Department of Information Systems Kampar Malaysia

ISBN: (纸本)9781665414074

It is common for pet owners to post about their missing pets on social media. When pets are found missing, pet owners usually need to physically search for their lost or missing pets. In order to overcome this problem, a pet location tracking system has been proposed to recover the lost pets. The aim of this study is to examine the success factors of information System (IS) namely System Quality, information Quality and Service Quality on mobile pet location tracking system. This research is significant because there is still a lack of attention to the unbearable consequences of losing a pet. The online questionnaire survey was used to collect data. The outcome of this study shows that System Quality and information Quality have the highest effect on the success of PLTS. © 2021 IEEE.

关键词： Location

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Machine-Learning-Based Prediction Models of Coronary Heart Disease Using Naïve Bayes and Random Forest Algorithms 7

Machine-Learning-Based Prediction Models of Coronary Heart D...

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7th International Conference on Software engineering and Computer systems and 4th International Conference on Computational Science and information management, ICSECS-ICOCSIM 2021

作者： Bemando, Charles Miranda, Eka Aryuni, Mediana Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9781665414074

Coronary heart disease (CHD), alternatively known as cardiovascular disease (CVD) is the number one cause of death in the world. Accordingly, a plethora of research have been conducted to predict the early diagnosis of the heart disease and determine the most important risk factors associated with the disease. Despite these considerable efforts, the accuracy of the prediction has remained inadequate and the most important risk factors have remained elusive. This research paper discusses many risk factors associated with the disease and presents the prediction models of coronary heart disease using supervised machine learning algorithms, namely Gaussian Naïve Bayes, Bernoulli Naïve Bayes and Random Forest algorithms. It uses the public dataset from the Cleveland database of UCI repository of coronary heart disease patients. The results show that the Gaussian Naïve Bayes, Bernoulli Naïve Bayes and Random Forest algorithms have accuracies of 85.00%, 85.00% and 75.00%, respectively. Moreover, the precision, F-measure and recall of the Gaussian and Bernoulli Naïve Bayes are higher than those of Random Forest algorithm, signifying its importance in predicting the early diagnosis of the disease. © 2021 IEEE.

关键词： Diseases

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