Showing papers in "Computer Science Review in 2019"

TL;DR: The most recent results of quantum computation technology are reviewed and the open problems of the field are addressed.

TL;DR: The proposed taxonomy makes it easier to understand the existing attack landscape towards developing defence mechanisms, and is leveraged to identify open problems that can lead to new research areas within the field of adversarial machine learning.

TL;DR: This study contributes towards identifying a unified taxonomy for security requirements, threats, vulnerabilities and countermeasures to carry out the proposed end-to-end mapping and highlights security challenges in other related areas like trust based security models, cloud-enabled applications of Big Data, Internet of Things, Software Defined Network (SDN) and Network Function Virtualization (NFV).

TL;DR: A detailed study on sophisticated attack and evasion techniques used by the contemporary malwares is presented and existing malware analysis techniques, application hardening techniques and CPU assisted application security schemes are discussed.

TL;DR: This work presents the detailed review of 50 research papers suggesting the methodologies, like Bayesian model, Fuzzy classifier, Artificial Neural Networks (ANN), Support Vector Machine (SVM) classifiers, Neural Network (NN), Machine Learning Methods and so on, based on stock market prediction.

TL;DR: A review on the continual development of context-aware recommender systems by analyzing different kinds of contexts without limiting to any specific application domain and what modification or additions are being applied on the top of conventional recommendation approaches to produce context- Aware recommendations.

TL;DR: This paper aims to summarise the efforts to date of applying ML and MAS to OGI tasks, identify possible reasons for their low and slow uptake and suggest ways to ensure a greater adoption of these technologies in the OGI.

TL;DR: UML ADs are not being used for non-functional testing, only a few approaches have been validated against realistic, industrial case studies, most approaches target very restricted application domains, and there is currently a clear lack of holistic approaches for model-based testing using U ML ADs.

TL;DR: An empirical analysis of publication metadata obtained from 6 top-tier journals and 9 conferences for the first 16 years of the 21st Century finds steady growth both in terms of productivity and impact, evidenced by the unabated number of publications/citations over the period of study.

TL;DR: An overview of Science of Scientific Team Science is presented, aiming at assisting scientific team formation, improving collaboration environment, evaluating team performance, and fostering collaborative behaviors, which gives rise to critical implications for scholars who wish to employ and invest in those issues.

TL;DR: A comprehensive taxonomy of the mitigation and detection mechanism of blackhole attack and its variants is presented along with summarization and comparison of some published work related to those categories.

TL;DR: A comprehensive survey of the previous research done to develop techniques for ensuring privacy of patient data that includes demographics data, diagnosis codes and the data containing both demographics and diagnosis codes is presented.

TL;DR: In this paper, the authors analyse methods and applications in data-driven prediction in the science of science, and discuss their significance, including open issues and existing challenges, and suggest potential research directions.

TL;DR: A survey on caching approaches and related issues like cache content, availability, and cache router localization and so on is presented to present a state-of-art research paper for researchers who are interested in the area of Information centric network.

TL;DR: This systematic mapping study focuses on 47 primary studies to identify the aim and the method of the API usability studies and investigates which API usability factors are evaluated, at which phases of API development is the usability of API evaluated and what are the current limitations and open issues in API usability evaluation.

TL;DR: A systematic literature review is performed, in which thirty-two articles with coherent outcomes associated with usability and security are selected and meaningful suggestions for realising a useable, secure and trustworthy password manager are presented.

TL;DR: An analysis of medical image modalities, such as Magnetic Resonance Imaging, that generate hundreds of images series is presented, through a Systematic Mapping that identifies methods and techniques currently being used in this scenario.

TL;DR: In this article, the authors discuss the use of Structural Equation Modeling (SEM) in providing an in-depth explanation of evaluation results and an explanation of failures and successes of a system; in particular, the case of evaluation of information retrieval systems.

TL;DR: A brief survey of the key research contributions to the design and the implementation of probability approximation methods is provided.

TL;DR: This is the first comparative study of the state-of-the-art Urdu stemmers, based on various distinct features such as used approach, main idea, limitations, the rules or affixes, data set, evaluation criteria and claimed accuracy.