2021 6th International Conference on Computer Science and Engineering (UBMK)最新文献_第10页

Convolutional Attention Network for MRI-based Alzheimer’s Disease Classification and its Interpretability Analysis 基于mri的阿尔茨海默病分类卷积注意网络及其可解释性分析

2021 6th International Conference on Computer Science and Engineering (UBMK) Pub Date : 2021-09-15 DOI: 10.1109/UBMK52708.2021.9558882

Yasemin Turkan, F. Tek

{"title":"Convolutional Attention Network for MRI-based Alzheimer’s Disease Classification and its Interpretability Analysis","authors":"Yasemin Turkan, F. Tek","doi":"10.1109/UBMK52708.2021.9558882","DOIUrl":"https://doi.org/10.1109/UBMK52708.2021.9558882","url":null,"abstract":"Neuroimaging techniques, such as Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET), help to identify Alzheimer’s disease (AD). These techniques generate large-scale, high-dimensional, multimodal neuroimaging data, which is time-consuming and difficult to interpret and classify. Therefore, interest in deep learning approaches for the classification of 3D structural MRI brain scans has grown rapidly. In this research study, we improved the 3D VGG model proposed by Korolev et al. [2]. We increased the filters in the 3D convolutional layers and then added an attention mechanism for better classification. We compared the performance of the proposed approaches for the classification of Alzheimer’s disease versus mild cognitive impairments and normal cohorts on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. We observed that both the accuracy and area under curve results improved with the proposed models. However, deep neural networks are black boxes that produce predictions that require further explanation for medical usage. We compared the 3D-data interpretation capabilities of the proposed models using four different interpretability methods: Occlusion, 3D Ultrametric Contour Map, 3D Gradient-Weighted Class Activation Mapping, and SHapley Additive exPlanations (SHAP). We observed that explanation results differed in different network models and data classes.","PeriodicalId":106516,"journal":{"name":"2021 6th International Conference on Computer Science and Engineering (UBMK)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116078874","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: 3

XML Document Transformation for Data Manipulation Operations 用于数据操作操作的XML文档转换

2021 6th International Conference on Computer Science and Engineering (UBMK) Pub Date : 2021-09-15 DOI: 10.1109/UBMK52708.2021.9559019

A. Mukhitova, A. Yerimbetova, Nenad Mladenović

引用次数: 0

Offensive Language Detection in Turkish Tweets with Bert Models 基于Bert模型的土耳其语推文攻击性语言检测

2021 6th International Conference on Computer Science and Engineering (UBMK) Pub Date : 2021-09-15 DOI: 10.1109/UBMK52708.2021.9559000

Anil Özberk, I. Çiçekli

引用次数: 10

A Review of Blockchain Based Solutions for Fight Against Pandemics 基于区块链的流行病防治解决方案综述

2021 6th International Conference on Computer Science and Engineering (UBMK) Pub Date : 2021-09-15 DOI: 10.1109/UBMK52708.2021.9558911

Seval Capraz, Adnan Özsoy

{"title":"A Review of Blockchain Based Solutions for Fight Against Pandemics","authors":"Seval Capraz, Adnan Özsoy","doi":"10.1109/UBMK52708.2021.9558911","DOIUrl":"https://doi.org/10.1109/UBMK52708.2021.9558911","url":null,"abstract":"Starting in late 2019, a highly infectious coronavirus disease spread rapidly to all over the world and caused many deaths worldwide. This disease known as COVID-19 caused more than 180 million cases including more than 4 million deaths. Numerous false reports, misinformation, and unsolicited fears in regards to coronavirus, are being circulated regularly since the outbreak of the COVID-19. We can solve some of the problems of the pandemic with new technologies like blockchain, therefore we can control its spread until an effective and affordable vaccine is found. Blockchain can combat pandemics by enabling early detection of outbreaks, protecting user privacy, and ensuring reliable medical supply chain during the outbreak tracking. When ill people are detected, it is possible to quickly and accurately share their diagnostic information and clinical presentation with blockchain. We can also hide patients’ identity while sharing that information. Anonymization is supported in blockchain and it’s stronger than other techniques. Moreover, blockchain is transparent so that every disease event can be kept tabs on transparently. There are a lot of blockchain solutions in literature which is proposed recently to combat COVID-19-like pandemics. In this study, we aim to give the details of blockchain and why we can use it for light against pandemics and review proposed solutions. We summarized the problems of pandemic and the benefits of blockchain technology. We highlighted the defects of solutions in literature and propose alternatives.","PeriodicalId":106516,"journal":{"name":"2021 6th International Conference on Computer Science and Engineering (UBMK)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124565747","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

Improving Text Classification with Transformer 用Transformer改进文本分类

2021 6th International Conference on Computer Science and Engineering (UBMK) Pub Date : 2021-09-15 DOI: 10.1109/UBMK52708.2021.9558906

Gokhan Soyalp, Artun Alar, Kaan Ozkanli, Beytullah Yildiz

引用次数: 5

Security and Privacy Challenges, Solutions, and Open Issues in Smart Metering: A Review 智能电表中的安全和隐私挑战、解决方案和开放问题:综述

2021 6th International Conference on Computer Science and Engineering (UBMK) Pub Date : 2021-09-15 DOI: 10.1109/UBMK52708.2021.9558912

Lae Lae Win, Samet Tonyali

引用次数: 3

Deep Learning Methods with Pre-Trained Word Embeddings and Pre-Trained Transformers for Extreme Multi-Label Text Classification 基于预训练词嵌入和预训练变形的深度学习方法用于极端多标签文本分类

2021 6th International Conference on Computer Science and Engineering (UBMK) Pub Date : 2021-09-15 DOI: 10.1109/UBMK52708.2021.9558977

Necdet Eren Erciyes, A. K. Görür

{"title":"Deep Learning Methods with Pre-Trained Word Embeddings and Pre-Trained Transformers for Extreme Multi-Label Text Classification","authors":"Necdet Eren Erciyes, A. K. Görür","doi":"10.1109/UBMK52708.2021.9558977","DOIUrl":"https://doi.org/10.1109/UBMK52708.2021.9558977","url":null,"abstract":"In recent years, there has been a considerable increase in textual documents online. This increase requires the creation of highly improved machine learning methods to classify text in many different domains. The effectiveness of these machine learning methods depends on the model capacity to understand the complex nature of the unstructured data and the relations of features that exist. Many different machine learning methods were proposed for a long time to solve text classification problems, such as SVM, kNN, and Rocchio classification. These shallow learning methods have achieved doubtless success in many different domains. For big and unstructured data like text, deep learning methods which can learn representations and features from the input data wtihout using any feature extraction methods have shown to be one of the major solutions. In this study, we explore the accuracy of recent recommended deep learning methods for multi-label text classification starting with simple RNN, CNN models to pretrained transformer models. We evaluated these methods’ performances by computing multi-label evaluation metrics and compared the results with the previous studies.","PeriodicalId":106516,"journal":{"name":"2021 6th International Conference on Computer Science and Engineering (UBMK)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126971288","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: 1

Software Log Classification in Telecommunication Industry 电信行业软件日志分类

2021 6th International Conference on Computer Science and Engineering (UBMK) Pub Date : 2021-09-15 DOI: 10.1109/UBMK52708.2021.9558985

Onur Ülkü, Necip Gözüaçik, Senem Tanberk, M. Aydin, A. Zaim

引用次数: 0

Controlling Shadow IT: Case Study from a Turkish Bank 控制影子IT:以一家土耳其银行为例

2021 6th International Conference on Computer Science and Engineering (UBMK) Pub Date : 2021-09-15 DOI: 10.1109/UBMK52708.2021.9558944

N. Ozkan, Kübra Bulut, M. Gök, G. Özer

引用次数: 1

Improved Resource Scheduling for Lightweight SMT-COP 改进轻量级SMT-COP的资源调度

2021 6th International Conference on Computer Science and Engineering (UBMK) Pub Date : 2021-09-15 DOI: 10.1109/UBMK52708.2021.9558934

Ugur Nezir, Burak Lus, Gurhan Kucuk

{"title":"Improved Resource Scheduling for Lightweight SMT-COP","authors":"Ugur Nezir, Burak Lus, Gurhan Kucuk","doi":"10.1109/UBMK52708.2021.9558934","DOIUrl":"https://doi.org/10.1109/UBMK52708.2021.9558934","url":null,"abstract":"Simultaneous multithreading (SMT) processors target resource under-utilization related performance problems of superscalar processors by allowing various datapath resources to be simultaneously shared among several threads with ease. This approach exploits thread-level parallelism on top of the well-studied instruction level parallelism. However, when datapath resources are shared among threads, there is always a possibility that corunning ill-intended programs may try to sniff on other programs with sensitive information like passwords or cryptocurrency information. By stress-testing and measuring many of the shared resources, this is quite achievable. These approaches are known as side-channel attacks. SMT-COP, a study published recently, is a secure architectural implementation based on resource scheduling that prevents these kind of attacks based on execution logic with a modest performance loss of nearly 10%. In this study, we aim to improve SMT-COP’s resource distribution scheme with several approaches, providing a quite close sense of security to that of SMT-COP while improving the performance by up to 8.86% on the average, over the original SMT-COP design.","PeriodicalId":106516,"journal":{"name":"2021 6th International Conference on Computer Science and Engineering (UBMK)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130825111","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: 1