2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)最新文献_第2页

Speed Control of DC Motor Using Improved Sine Cosine Algorithm Based PID Controller 基于改进正弦余弦算法的PID控制器的直流电动机速度控制

2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) Pub Date : 2019-10-01 DOI: 10.1109/ISMSIT.2019.8932907

Serdar Ekinci, B. Hekimoğlu, A. Demirören, Erdal Eker

引用次数: 10

Image based guidance for near rendezvous and docking of spacecraft 基于图像的航天器近交会对接制导

2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) Pub Date : 2019-10-01 DOI: 10.1109/ISMSIT.2019.8932816

Harun Çelik

引用次数: 0

Open-Source Web-Based Software for Performing Permutation Tests 用于执行排列测试的基于web的开源软件

2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) Pub Date : 2019-10-01 DOI: 10.1109/ISMSIT.2019.8932946

Z. Tunç, Şeyma Yaşar, C. Colak

{"title":"Open-Source Web-Based Software for Performing Permutation Tests","authors":"Z. Tunç, Şeyma Yaşar, C. Colak","doi":"10.1109/ISMSIT.2019.8932946","DOIUrl":"https://doi.org/10.1109/ISMSIT.2019.8932946","url":null,"abstract":"In this study, it is aimed to develop a new user-friendly web-based software which can overcome the difficulties of use due to the limitations in the use stages of parametric and non-parametric tests and can easily use the permutation tests which can be used as an alternative to these tests.Shiny, an open-source R package, is used to develop the recommended web software. In the developed software, by selecting \"the Specify Sample Number\" tab, the number of samples presented as \"Single\", \"Two\" and \"More than two\" options is selected and analyzes are made by selecting the appropriate data set from the file upload menu.In this study, in order to show the way the software works and to evaluate its outputs, a data set containing 1000 observations with the standard normal distribution of variables consisting of two variables was used. \"Two Dependent Sample Permutation Tests\" were selected to analyze whether there was any difference between the variables. According to the results, no statistically significant difference was found between the variables.The developed software is a new user-friendly web-based software that can be used to perform the permutation tests in an easy way as an alternative to parametric and non-parametric tests.","PeriodicalId":169791,"journal":{"name":"2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114067747","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}

引用次数: 0

Perimeter Network Security Solutions: A Survey 周界网络安全解决方案:调查

2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) Pub Date : 2019-10-01 DOI: 10.1109/ISMSIT.2019.8932821

Goksel Uctu, M. Alkan, I. Dogru, Murat Dörterler

引用次数: 3

Performance Comparison of Phase-Shifted Carrier PWM Techniques on Cascaded H-Bridge Multilevel Inverters with Unequal DC Voltages 非等直流电压级联h桥多电平逆变器移相载波PWM技术的性能比较

2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) Pub Date : 2019-10-01 DOI: 10.1109/ISMSIT.2019.8932903

F. Eroǧlu, M. Kurtoglu, A. O. Arslan, Ahmet Mete Vural

引用次数: 0

Classification and Success Investigation of Biomedical Data Sets Using Supervised Machine Learning Models 使用监督机器学习模型的生物医学数据集分类和成功研究

2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) Pub Date : 2019-10-01 DOI: 10.1109/ISMSIT.2019.8932734

Sarmad N. Mohammed, Mehmet Serdar Guzel, E. Bostanci

引用次数: 2

Sentence Classification with Deep Learning Method For Virtual Assistant Applications 基于深度学习方法的句子分类虚拟助手应用

2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) Pub Date : 2019-10-01 DOI: 10.1109/ISMSIT.2019.8932888

Gurur Pi̇rana, A. Sertbas, T. Ensari

{"title":"Sentence Classification with Deep Learning Method For Virtual Assistant Applications","authors":"Gurur Pi̇rana, A. Sertbas, T. Ensari","doi":"10.1109/ISMSIT.2019.8932888","DOIUrl":"https://doi.org/10.1109/ISMSIT.2019.8932888","url":null,"abstract":"This paper investigates three different deep learning method performance for virtual assistant applications about sentence classification. The classification is based in Turkish texts. For three different model we demonstrate the performance of each model. We investigate Convolutional Neural Network (CNN), Region Convolutional Neural Network (RCNN) and Long Short Term Memory (LSTM) deep learning methods and compare the accuracy results of the related models. Furthermore, we aim to select the best classification model for our dataset.We have researched effect of the hyper parameters to model accuracy and we used best hyper parameters for each methods and we aimed to gain best performance for our dataset.This resarch helps applications like virtual assistant with classification of the sentence and giving the output of the class. The output of classification could be a text, image or document. Benefit of this comparsion of the methods we realized that instance number increses the model accuracy. The best method for our dataset was the Convolutional Neural Networks (CNN) with the %87.3 accuracy.","PeriodicalId":169791,"journal":{"name":"2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129406339","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}

引用次数: 2

Network Anomaly Detection System using Genetic Algorithm, Feature Selection and Classification 网络异常检测系统采用遗传算法、特征选择和分类

2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) Pub Date : 2019-10-01 DOI: 10.1109/ISMSIT.2019.8932750

Elif Uysal, Gülnur Demircioğlu, Gulsade Kale, E. Bostanci, M. Güzel, Sarmad N. Mohammed

{"title":"Network Anomaly Detection System using Genetic Algorithm, Feature Selection and Classification","authors":"Elif Uysal, Gülnur Demircioğlu, Gulsade Kale, E. Bostanci, M. Güzel, Sarmad N. Mohammed","doi":"10.1109/ISMSIT.2019.8932750","DOIUrl":"https://doi.org/10.1109/ISMSIT.2019.8932750","url":null,"abstract":"Networks are dangerous environments with containing numerous security vulnerabilities and those vulnerabilities are likely to be used while attacking systems with the intent of stealing valuable information or stopping the services. A system should be protected from already-known types of attacks and also have ability to detect unknown types of attacks to prevent abduction of the information. Unknown types of attacks may give harm to the system by stopping the services that runs effective and stable. For that purpose, it has become necessary to develop a flexible and adaptable system which can collect instant data from the network, distinguish between harmless and harmful behaviors and take measures against them. The main goal of this work is to explain a network anomaly detection system that is developed using genetic algorithm and Weka classification features to fulfill the purposes stated above. The Genetic Algorithm is used to generate various individuals with the aim of determining which attributes of the individual are providing a better result about learning the behavioral pattern of the network traffic. Furthermore, Weka classifiers are applied to the train and test datasets to calculate the best fitness value, and to decide on individual's attributes that are more effective about finding the anomaly occurring in a given instant.","PeriodicalId":169791,"journal":{"name":"2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132814548","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}

引用次数: 2

A Survey on Keyword and Key Phrase Extraction with Deep Learning 基于深度学习的关键词和关键短语提取研究综述

2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) Pub Date : 2019-10-01 DOI: 10.1109/ISMSIT.2019.8932811

Özlem Kilic, Aydın Çetin

{"title":"A Survey on Keyword and Key Phrase Extraction with Deep Learning","authors":"Özlem Kilic, Aydın Çetin","doi":"10.1109/ISMSIT.2019.8932811","DOIUrl":"https://doi.org/10.1109/ISMSIT.2019.8932811","url":null,"abstract":"With the technological developments, a large amount of data has been produced. Tera bytes of data previously recorded by manpower were digitized with the use of personal computers. As a result, rapidly growing data stacks were formed, making it difficult to find information among these unanticipated data. The need to make sense of this data has made predefined statistical methods more important. It is possible to access the required information from a single document or from the document stacks by means of text mining methods. This problem, which was previously solved mostly by statistical methods or Natural Language Processing (NLP) techniques, has been started to be solved by machine learning algorithms and artificial neural networks. In recent years, deep learning, which is a specialized study area of artificial neural networks, gives better results than the current statistical and NLP methods in many problems and has provided the application of these methods in problems such as machine translation, keyword extraction and summarizing. In this study, deep learning methods used in the extraction of keywords and key phrases are examined.","PeriodicalId":169791,"journal":{"name":"2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128883830","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}

引用次数: 6

Keratinocyte Carcinoma Detection via Convolutional Neural Networks 角化细胞癌的卷积神经网络检测

2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) Pub Date : 2019-10-01 DOI: 10.1109/ISMSIT.2019.8932828

Ali Serener, Sertan Serte

引用次数: 8