Hybrid journal (It can contain Open Access articles) ISSN (Print) 1751-3227 - ISSN (Online) 1751-3235 Published by Inderscience Publishers[451 journals]
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Authors:Anjana Gosain, Kriti Saroha Pages: 93 - 105 Abstract: Bitemporal data warehouse (BTDW) design that extends the multidimensional model uses bitemporal (combination of valid time and transaction time) timestamps on the members of multidimensional data in order to manage time-varying data. Various approaches to manage changes of schema and dimension data in BTDW exist that use the combination of both valid-time as well as transaction time. Also, measures/facts can undergo change with time however current BTDWs do not handle or track changes for dynamic measures. This would pose problem for applications like fraud detection, where it is required to know and record the time when changes have occurred in the system; schema, dimension data or measures. Thus, the changes occurring in the measures need to be recorded indicating <i>the time when a specific measure value is valid or updated</i>. In this work, we propose solution for handling time-varying measures using bi-temporal versioning of fact table schema and fact data along with storage options for handling and storing the separate versions of fact table schema and data. Keywords: data warehouse; bitemporal data warehouse; BTDW; schema versioning; transaction time; valid-time; bitemporal; facts; measures Citation: International Journal of Information Systems and Management, Vol. 2, No. 2 (2020) pp. 93 - 105 PubDate: 2020-10-23T23:20:50-05:00 DOI: 10.1504/IJISAM.2020.110529 Issue No:Vol. 2, No. 2 (2020)
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Authors:Soha Ahmed, Shimaa Ouf, Yehai Helmy, Mahmoud Abd Ellatif Pages: 106 - 138 Abstract: The governmental sector is suffering from the lack of reliance on technology resources, in complex financial processes, like the budget process which is still prepared using the traditional way, which is paper-based, has a lack of technical aspect, and consumes time so unreal budget estimation has resulted. On the other hand, semantic web technology proved itself and achieved great success in many domains. Ontology is considered the backbone of the semantic web and is defined as a shared understanding of a domain that could help to store, retrieve, share, and reuse knowledge of a domain in an effective way. In this paper, ontology is used for the first time to build a budget ontological model to represent the public budget structure for the Egyptian public sector domain and make budget knowledge more accessible and usable, in order to enhance the integrity, transparency, reliability, and accuracy of the governmental public budget. Keywords: Egyptian public budget; ontology; budget ontology; financial ontology; business ontology; software architecture; semantic web; semantic metadata; SPARQL; owl viz Citation: International Journal of Information Systems and Management, Vol. 2, No. 2 (2020) pp. 106 - 138 PubDate: 2020-10-23T23:20:50-05:00 DOI: 10.1504/IJISAM.2020.110532 Issue No:Vol. 2, No. 2 (2020)
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Authors:Soha Ahmed, Shimaa Ouf, Yehai Helmy, Mahmoud Abd Ellatif Pages: 139 - 149 Abstract: Network traffic classification has been used for more than two decades for various applications, including QoS provisioning, anomaly detection, billing systems, etc. With the wide-spread adaptation of deep learning models in various fields, researchers also started adopting deep models for traffic classification task. However, the biggest challenge with deep models is that they need considerably larger training data in comparison with classical machine learning algorithms. In this paper, we propose a two-step training process that significantly reduces the number of labelled training samples. In the first step, we train a convolutional auto-encoder with an unlabelled and large public dataset. Then, in the second step, we transfer the models weights to a CNN model and we train the CNN model with only a few labelled samples. We compared our approach with two state-of-the-art methods and we showed that our approach outperforms. Keywords: traffic classification; convolutional auto-encoders; convolutional neural networks; CNNs; deep learning; encrypted traffic identification Citation: International Journal of Information Systems and Management, Vol. 2, No. 2 (2020) pp. 139 - 149 PubDate: 2020-10-23T23:20:50-05:00 DOI: 10.1504/IJISAM.2020.110551 Issue No:Vol. 2, No. 2 (2020)
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Authors:Eunyoung Moon, James Howison Pages: 150 - 184 Abstract: Increasingly complicated software makes it difficult to attract or maintain open source software (OSS) contributors. Faced with such challenges of increasingly complicated software design, large-scale refactoring that radically restructures the architecture of the software can be one of the solutions. In this study, we investigate and illustrate how OSS contributors accomplish large-scale refactoring in OSS development in which there is no significant corporate participation. In our observations, as the costs of coordination requirements rise, OSS contributors increase coordination capability to manage dependencies among multiple sources during the large-scale refactoring periods. Our findings suggest that OSS contributors episodically use traditional coordination mechanisms during the large-scale refactoring periods. Our study provides actionable insights into how OSS contributors make joint action that cannot be achieved by individuals working independently and use the provision of rewards in order to achieve a shared, explicit goal of large-scale refactoring. Keywords: collaborative work; online communities; coordination; open source; software refactoring Citation: International Journal of Information Systems and Management, Vol. 2, No. 2 (2020) pp. 150 - 184 PubDate: 2020-10-23T23:20:50-05:00 DOI: 10.1504/IJISAM.2020.110552 Issue No:Vol. 2, No. 2 (2020)
Hybrid journal (It can contain Open Access articles)
[451 journals]
