IADIS-International Journal on Computer Science and Information Systems最新文献_第2页

PERFORMANCE IMPROVEMENTS OF BIGBLUEBUTTON FOR DISTANCE TEACHING 远程教学中bigbluebutton的性能改进

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IADIS-International Journal on Computer Science and Information Systems Pub Date : 2022-07-27 DOI: 10.33965/ijcsis_2022170101

Christian Uhl, Bernd Freisleben

引用次数: 0

THE APPLICATION OF MACHINE LEARNING IN LITERATURE REVIEWS: A FRAMEWORK 机器学习在文献综述中的应用:一个框架

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IADIS-International Journal on Computer Science and Information Systems Pub Date : 2022-07-27 DOI: 10.33965/ijcsis_2022170105

Yusuf Bozkurt, Reiner Braun, Alexander Rossmann

{"title":"THE APPLICATION OF MACHINE LEARNING IN LITERATURE REVIEWS: A FRAMEWORK","authors":"Yusuf Bozkurt, Reiner Braun, Alexander Rossmann","doi":"10.33965/ijcsis_2022170105","DOIUrl":"https://doi.org/10.33965/ijcsis_2022170105","url":null,"abstract":"Literature reviews are essential for any scientific work, both as part of a dissertation or as a stand-alone work. Scientists benefit from the fact that more and more literature is available in electronic form, and finding and accessing relevant literature has become more accessible through scientific databases. However, a traditional literature review method is characterized by a highly manual process, while technologies and methods in big data, machine learning, and text mining have advanced. Especially in areas where research streams are rapidly evolving, and topics are becoming more comprehensive, complex, and heterogeneous, it is challenging to provide a holistic overview and identify research gaps manually. Therefore, we have developed a framework that supports the traditional approach of conducting a literature review using machine learning and text mining methods. The framework is particularly suitable in cases where a large amount of literature is available, and a holistic understanding of the research area is needed. The framework consists of several steps in which the critical mind of the scientist is supported by machine learning. The unstructured text data is transformed into a structured form through data preparation realized with text mining, making it applicable for various machine learning techniques. A concrete example in the field of smart cities makes the framework tangible.","PeriodicalId":41878,"journal":{"name":"IADIS-International Journal on Computer Science and Information Systems","volume":"21 1","pages":""},"PeriodicalIF":0.2,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86036967","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

SPECTRAL-SPATIAL CLASSIFICATION OF HYPERSPECTRAL DATA USING 3D-2D CONVOLUTIONAL NEURAL NETWORK AND INCEPTION NETWORK 基于3d-2d卷积神经网络和初始网络的高光谱数据光谱空间分类

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IADIS-International Journal on Computer Science and Information Systems Pub Date : 2021-11-01 DOI: 10.33965/ijcsis_2021160203

Douglas Omwenga, Guohua Liu

{"title":"SPECTRAL-SPATIAL CLASSIFICATION OF HYPERSPECTRAL DATA USING 3D-2D CONVOLUTIONAL NEURAL NETWORK AND INCEPTION NETWORK","authors":"Douglas Omwenga, Guohua Liu","doi":"10.33965/ijcsis_2021160203","DOIUrl":"https://doi.org/10.33965/ijcsis_2021160203","url":null,"abstract":"Hyperspectral imaging (HSI) classification has recently become a field of interest in the remote sensing (RS) community. However, such data contain multidimensional dynamic features that make it difficult for precise identification. Also, it covers structurally nonlinear affinity within the gathered spectral bands and the related materials. To systematically facilitate the HSI categorization, we propose a spectral-spatial classification of HSI data using a 3D-2D convolutional neural network and inception network to extract and learn the in-depth spectral-spatial feature vectors. We first applied the principal component analysis (PCA) on the entire HSI image to reduce the original space dimensionality. Second, the exploitation of the spatial hyperspectral input features contiguous information by 2-D CNN. Besides, we used 3-D CNN without relying on any preprocessing to extract deep spectral-spatial fused features efficiently. The learned spectral-spatial characteristics are concatenated and fed to the inception network layer for joint spectral-spatial learning. Furthermore, we learned and achieved the correct classification with a softmax regression classifier. Finally, we evaluated our model performance on different training set sizes of two hyperspectral remote sensing data sets (HSRSI), namely Botswana (BT) and Kennedy Space Center (KSC), and compared the experimental results with deep learning-based and state-of-the-art (SOTA) classification methods. The experiment results show that our model provides competitive classification results with state-of-the-art techniques, demonstrating the considerable potential for HSRSI classification.","PeriodicalId":41878,"journal":{"name":"IADIS-International Journal on Computer Science and Information Systems","volume":"8 1","pages":""},"PeriodicalIF":0.2,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78999145","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

HUMAN FACTORS ENGINEERING PROGRAM DEVELOPMENT AND USER INVOLVEMENT IN DESIGN OF AUTOMATIC TRAM 人因工程程序开发及用户参与自动有轨电车设计

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IADIS-International Journal on Computer Science and Information Systems Pub Date : 2021-11-01 DOI: 10.33965/ijcsis_2021160205

Hanna Koskinen, S. Aromaa, V. Goriachev

引用次数: 0

REVEALING BAND AND CIRCUMPLEX PATTERNS IN REORDERABLE MATRICES USING POLAR SORT AND FAST MULTIDIMENSIONAL PROJECTIONS 利用极排序和快速多维投影揭示可重排序矩阵中的带状和环状模式

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IADIS-International Journal on Computer Science and Information Systems Pub Date : 2021-11-01 DOI: 10.33965/ijcsis_2021160201

C. G. Silva

{"title":"REVEALING BAND AND CIRCUMPLEX PATTERNS IN REORDERABLE MATRICES USING POLAR SORT AND FAST MULTIDIMENSIONAL PROJECTIONS","authors":"C. G. Silva","doi":"10.33965/ijcsis_2021160201","DOIUrl":"https://doi.org/10.33965/ijcsis_2021160201","url":null,"abstract":"Analysts may use matrix-based visualizations (such as heatmaps) to reveal patterns of a dataset with the help of reordering algorithms that permute matrix rows and columns properly. One of these algorithms is Polar Sort, a pattern-focused reordering method that uses a multidimensional projection technique – Classical MDS – to reveal Band and Circumplex patterns in reorderable matrices. Despite its good reordering results regarding the mentioned patterns, Polar sort is not scalable due to Classical MDS’ asymptotic time complexity (O(n3) for an input matrix with size n × n). In this paper, we propose a new version of this algorithm, in which we replace Classical MDS with FastMap, a method with asymptotic time complexity O(n). The new algorithm (Polar Sort with Fastmap, or PSF for short) permutes rows and columns according to their bidimensional projections and uses a barycenter-based ordering identical to Polar Sort’s approach. The results of an experiment indicate that PSF maintained the output quality of Polar Sort regarding minimal span loss function, Moore stress, and circular correlation when reordering synthetic matrices. Besides, PSF’s asymptotic time complexity is O(n log n). This complexity is coherent with our experiment results, which point out that PSF had lower execution time than other compared methods. We also show some examples in which real-world matrices reordered by PSF revealed patterns similar to Band and Circumplex.","PeriodicalId":41878,"journal":{"name":"IADIS-International Journal on Computer Science and Information Systems","volume":"43 1","pages":""},"PeriodicalIF":0.2,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80194299","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

3D SCENE RECONSTRUCTION SYSTEM BASED ON A MOBILE DEVICE 基于移动设备的三维场景重建系统

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IADIS-International Journal on Computer Science and Information Systems Pub Date : 2021-11-01 DOI: 10.33965/ijcsis_2021160202

Damiano Oriti, A. Sanna, Francesco De Pace, Federico Manuri, Francesco Tamburello, Fabrizio Ronzino

{"title":"3D SCENE RECONSTRUCTION SYSTEM BASED ON A MOBILE DEVICE","authors":"Damiano Oriti, A. Sanna, Francesco De Pace, Federico Manuri, Francesco Tamburello, Fabrizio Ronzino","doi":"10.33965/ijcsis_2021160202","DOIUrl":"https://doi.org/10.33965/ijcsis_2021160202","url":null,"abstract":"Augmented reality (AR) and virtual reality (VR) applications can take advantage of efficient digitalization of real objects as reconstructed elements can allow users a better connection between real and virtual worlds than using pre-set 3D CAD models. Technology advances contribute to the spread of AR and VR technologies, which are always more diffuse and popular. On the other hand, the design and implementation of virtual and extended worlds is still an open problem; affordable and robust solutions to support 3D object digitalization is still missing. This work proposes a reconstruction system that allows users to receive a 3D CAD model starting from a single image of the object to be digitalized and reconstructed. A smartphone can be used to take a photo of the object under analysis and a remote server performs the reconstruction process by exploiting a pipeline of three Deep Learning methods. Accuracy and robustness of the system have been assessed by several experiments and the main outcomes show how the proposed solution has a comparable accuracy (chamfer distance) with the state-of-the-art methods for 3D object reconstruction.","PeriodicalId":41878,"journal":{"name":"IADIS-International Journal on Computer Science and Information Systems","volume":"29 1","pages":""},"PeriodicalIF":0.2,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75641179","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

IMPROVEMENT OF CLUSTERING ALGORITHMS BY IMPLEMENTATION OF SPELLING BASED RANKING 基于拼写排序的聚类算法改进

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IADIS-International Journal on Computer Science and Information Systems Pub Date : 2021-11-01 DOI: 10.33965/ijcsis_2021160204

Eva Bryer, Theppatorn Rhujittawiwat, J. Rose, Colin Wilder

{"title":"IMPROVEMENT OF CLUSTERING ALGORITHMS BY IMPLEMENTATION OF SPELLING BASED RANKING","authors":"Eva Bryer, Theppatorn Rhujittawiwat, J. Rose, Colin Wilder","doi":"10.33965/ijcsis_2021160204","DOIUrl":"https://doi.org/10.33965/ijcsis_2021160204","url":null,"abstract":"The goal of this paper is to modify an existing clustering algorithm with the use of the Hunspell spell checker to specialize it for the use of cleaning early modern European book title data. Duplicate and corrupted data is a constant concern for data analysis, and clustering has been identified to be a robust tool for normalizing and cleaning data such as ours. In particular, our data comprises over 5 million books published in European languages between 1500 and 1800 in the Machine-Readable Cataloging (MARC) data format from 17,983 libraries in 123 countries. However, as each library individually catalogued their records, many duplicative and inaccurate records exist in the data set. Additionally, each language evolved over the 300-year period we are studying, and as such many of the words had their spellings altered. Without cleaning and normalizing this data, it would be difficult to find coherent trends, as much of the data may be missed in the query. In previous research, we have identified the use of Prediction by Partial Matching to provide the most increase in base accuracy when applied to dirty data of similar construct to our data set. However, there are many cases in which the correct book title may not be the most common, either when only two values exist in a cluster, or the dirty title exists in more records. In these cases, a language agnostic clustering algorithm would normalize the incorrect title and lower the overall accuracy of the data set. By implementing the Hunspell spell checker into the clustering algorithm, using it to rank clusters by the number of words not found in their dictionary, we can drastically lower the cases of this occurring. Indeed, this ranking algorithm proved to increase the overall accuracy of the clustered data by as much as 25% over the unmodified Prediction by Partial Matching algorithm.","PeriodicalId":41878,"journal":{"name":"IADIS-International Journal on Computer Science and Information Systems","volume":"33 1","pages":""},"PeriodicalIF":0.2,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76916636","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

DESIGN AND PROTOTYPING OF WEB-BASED SUPPORT FOR SHIP-HANDLING SYSTEM VIA MOBILE WIRELESS COMMUNICATION 基于移动无线通信的船舶装卸系统网络支持的设计与原型

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IADIS-International Journal on Computer Science and Information Systems Pub Date : 2021-11-01 DOI: 10.33965/ijcsis_2021160206

Tsuyoshi Miyashita, Ryota Imai, Masaki Kondo, Tadasuke Furuya

引用次数: 0

DYNAMIC CONNECTIVITY: SOME GRAPHS OF INTEREST 动态连接:一些感兴趣的图

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IADIS-International Journal on Computer Science and Information Systems Pub Date : 2021-01-26 DOI: 10.33965/ijcsis_2021160101

G. Lagogiannis

引用次数: 0

MITIGATING THE INSIDER THREAT TO INFORMATION SYSTEMS USING FULLY EMBEDDED AND INSEPARABLE AUTONOMIC SELF-PROTECTION CAPABILITY 利用完全嵌入式和不可分割的自主自我保护能力减轻信息系统的内部威胁

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IADIS-International Journal on Computer Science and Information Systems Pub Date : 2021-01-26 DOI: 10.33965/ijcsis_2021160106

G. Jabbour, Jason J. Jabbour

{"title":"MITIGATING THE INSIDER THREAT TO INFORMATION SYSTEMS USING FULLY EMBEDDED AND INSEPARABLE AUTONOMIC SELF-PROTECTION CAPABILITY","authors":"G. Jabbour, Jason J. Jabbour","doi":"10.33965/ijcsis_2021160106","DOIUrl":"https://doi.org/10.33965/ijcsis_2021160106","url":null,"abstract":"The insider threat is a problem that organizations have to deal with. Regardless of its size, mission, or location, any company that uses information systems is potentially vulnerable to insider attacks. Federal agencies, non-governmental organizations, as well as data centers face the same risk of being attacked by an insider. Countering the insider threat is a difficult and daunting task. Organizations concerned with the problem usually train their employees on security-related matters, rules of behavior policies, and the consequences of committing criminal activities. More technically-oriented solutions include enhanced credentialing and access control, and the use of monitoring tools that provide insight into the health and status of systems. This paper addresses the deficiency of widely-used monitoring tools and strategies. It discusses the difference between traditional security approaches and autonomic-based self-protection. The paper then proposes a solution that equips a system with innate self-defense mechanisms that relieve the system from having to rely on human intervention. The paper introduces the Insider Threat Minimization and Mitigation Framework. This framework equips systems with self-defense mechanisms such that a system can instantaneously respond to potential threats and defend itself against users who have unfettered access to it. The framework employs the autonomous demotion of power users’ access privileges based on analysis and evaluation of the user’s risk level. The paper presents the details of the proposed framework and simulates its effectiveness within a data center environment of mission-critical systems.","PeriodicalId":41878,"journal":{"name":"IADIS-International Journal on Computer Science and Information Systems","volume":"51 1","pages":""},"PeriodicalIF":0.2,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88881081","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