2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)最新文献_第3页

A Design and Implementation of Performance Dashboard for the Work Integrated Learning Unit 工作综合学习单元绩效仪表板的设计与实现

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982514

Pathathai Na-Lumpoon, Pree Thiengburanathum

引用次数: 0

Deep Learning with Convolutional Neural Network and Long Short-Term Memory for Phishing Detection 基于卷积神经网络和长短期记忆的深度学习网络钓鱼检测

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982427

Moruf Akin Adebowale, Khin T. Lwin, Mohammed Alamgir Hossain

引用次数: 19

A Simultaneous Approach for Compression and Encryption Techniques Using Deoxyribonucleic Acid 一种同时使用脱氧核糖核酸的压缩和加密技术

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982392

D. A. Zebari, H. Haron, D. Zeebaree, A. Zain

{"title":"A Simultaneous Approach for Compression and Encryption Techniques Using Deoxyribonucleic Acid","authors":"D. A. Zebari, H. Haron, D. Zeebaree, A. Zain","doi":"10.1109/SKIMA47702.2019.8982392","DOIUrl":"https://doi.org/10.1109/SKIMA47702.2019.8982392","url":null,"abstract":"The Data Compression is a creative skill which defined scientific concepts of providing contents in a compact form. Thus, it has turned into a need in the field of communication as well as in different scientific studies. Data transmission must be sufficiently secure to be utilized in a channel medium with no misfortune; and altering of information. Encryption is the way toward scrambling an information with the goal that just the known receiver can peruse or see it. Encryption can give methods for anchoring data. Along these lines, the two strategies are the two crucial advances that required for the protected transmission of huge measure of information. In typical cases, the compacted information is encoded and transmitted. In any case, this sequential technique is time consumption and computationally cost. In the present paper, an examination on simultaneous compression and encryption technique depends on DNA which is proposed for various sorts of secret data. In simultaneous technique, both techniques can be done at single step which lessens the time for the whole task. The present work is consisting of two phases. First phase, encodes the plaintext by 6-bits instead of 8-bits, means each character represented by three DNA nucleotides whereas to encode any pixel of image by four DNA nucleotides. This phase can compress the plaintext by 25% of the original text. Second phase, compression and encryption has been done at the same time. Both types of data have been compressed by their half size as well as encrypted the generated symmetric key. Thus, this technique is more secure against intruders. Experimental results show a better performance of the proposed scheme compared with standard compression techniques.","PeriodicalId":245523,"journal":{"name":"2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126884938","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: 19

Towards Dynamic Fit Assessment for Strategic Alignment using Enterprise Architecture Models 利用企业架构模型实现战略一致性的动态契合评估

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982388

Dóra Ori, Z. Szabó

引用次数: 0

An automatic cluster-based approach for depth estimation of single 2D images 一种基于自动聚类的二维图像深度估计方法

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982472

Muhammad Awais Shoukat, Allah Bux Sargano, Z. Habib, L. You

{"title":"An automatic cluster-based approach for depth estimation of single 2D images","authors":"Muhammad Awais Shoukat, Allah Bux Sargano, Z. Habib, L. You","doi":"10.1109/SKIMA47702.2019.8982472","DOIUrl":"https://doi.org/10.1109/SKIMA47702.2019.8982472","url":null,"abstract":"In this paper, the problem of single 2D image depth estimation is considered. This is a very important problem due to its various applications in the industry. Previous learning-based methods are based on a key assumption that color images having photometric resemblance are likely to present similar depth structure. However, these methods search the whole dataset for finding corresponding images using handcrafted features, which is quite cumbersome and inefficient process. To overcome this, we have proposed a clustering-based algorithm for depth estimation of a single 2D image using transfer learning. To realize this, images are categorized into clusters using K-means clustering algorithm and features are extracted through a pre-trained deep learning model i.e., ResNet-50. After clustering, an efficient step of replacing feature vector is embedded to speedup the process without compromising on accuracy. After then, images with similar structure as an input image, are retrieved from the best matched cluster based on their correlation values. Then, retrieved candidate depth images are employed to initialize prior depth of a query image using weighted-correlation-average (WCA). Finally, the estimated depth is improved by removing variations using cross-bilateral-filter. In order to evaluate the performance of proposed algorithm, experiments are conducted on two benchmark datasets, NYU v2 and Make3D.","PeriodicalId":245523,"journal":{"name":"2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129146773","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

Local Differentially Private Matrix Factorization For Recommendations 推荐的局部微分私有矩阵分解

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982536

N. Jeyamohan, Xiaomin Chen, N. Aslam

引用次数: 2

Partitioning based incremental marginalization algorithm for anonymizing missing data streams 基于分区的缺失数据流匿名化增量边缘化算法

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982399

Ankhbayar Otgonbayar, Zeeshan Pervez, K. Dahal

{"title":"Partitioning based incremental marginalization algorithm for anonymizing missing data streams","authors":"Ankhbayar Otgonbayar, Zeeshan Pervez, K. Dahal","doi":"10.1109/SKIMA47702.2019.8982399","DOIUrl":"https://doi.org/10.1109/SKIMA47702.2019.8982399","url":null,"abstract":"The IoT and its applications are the inseparable part of modern world. IoT is expanding into every corner of the world where internet is available. IoT data streams are utilized by many organizations for research and business. To benefit from these data streams, the data handling party must secure the individuals’ privacy. The most common privacy preservation approach is data anonymization. However, IoT data provides missing data streams due to the varying device pool and preferences of individuals and unpredicted devices’ malfunctions of IoT. Minimization of missingess and information loss is very important for anonymizing of missing data streams. To achieve this, we introduce IncrementalPBM (Incremental Partitioning Based Marginalization) for anonymizing missig data streams. IncrementalPBM utilizes time based sliding window for missing data stream anonymization, and it aims to control the number of QIDs for anonymization while increasing the number of tuples for anonymization. Our experiment on real dataset showed IncrementalPBM is effective and efficient for anonymizing missing data streams compared to existing missing data stream anonymization algorithm. IncrementalPBM showed significant improvement; 5% to 9% less information loss, 4500 to 6000 more number of re-use anonymization while showing comparable clustering, suppression and runtime.","PeriodicalId":245523,"journal":{"name":"2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114656416","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

On the Solution of Poisson’s Equation using Deep Learning 用深度学习求解泊松方程

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982518

Riya Aggarwal, H. Ugail

引用次数: 4

A Deep Learning Approach to Tumour Identification in Fresh Frozen Tissues 新鲜冷冻组织肿瘤识别的深度学习方法

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982508

H. Ugail, Maisun Alzorgani, A. M. Bukar, Humera Hussain, Christopher Burn, Thinzar Min Sein, S. Betmouni

{"title":"A Deep Learning Approach to Tumour Identification in Fresh Frozen Tissues","authors":"H. Ugail, Maisun Alzorgani, A. M. Bukar, Humera Hussain, Christopher Burn, Thinzar Min Sein, S. Betmouni","doi":"10.1109/SKIMA47702.2019.8982508","DOIUrl":"https://doi.org/10.1109/SKIMA47702.2019.8982508","url":null,"abstract":"The demand for pathology services are significantly increasing whilst the numbers of pathologists are significantly decreasing. In order to overcome these challenges, a growing interest in faster and efficient diagnostic methods such as computer-aided diagnosis (CAD) have been observed. An increase in the use of CAD systems in clinical settings has subsequently led to a growing interest in machine learning. In this paper, we show the use of machine learning algorithms in the prediction of tumour content in Fresh Frozen (FF) histological samples of head and neck. More specifically, we explore a pre-trained convolutional neural network (CNN), namely the AlexNet, to build two common machine learning classifiers. For the first classifier, the pre-trained AlexNet network is used to extract features from the activation layer and then Support Vector Machine (SVM) based classifier is trained by using these extracted features. In the second case, we replace the last three layers of the pre-trained AlexNet network and then fine tune these layers on the FF histological image samples. The results of our experiments are very promising. We have obtained percentage classification rates in the high 90s, and our results show there is little difference between SVM and transfer learning. Thus, the present study show that an AlexNet driven CNN with SVM and fine-tuned classifiers are a suitable choice for accurate discrimination between tumour and non-tumour histological samples from the head and neck.","PeriodicalId":245523,"journal":{"name":"2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114933728","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

IoT Based Remote Medical Diagnosis System Using NodeMCU 基于物联网的NodeMCU远程医疗诊断系统

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982509

Fahim Faisal, S. A. Hossain

引用次数: 5