Amira Dhokar, Lobna Hlaoua, Lotfi Ben Romdhane.

Nowadays, social medias are very popular amon g their users. One of the most well -known social networks is Twitter. It is a micro-blog that enables its users to send short messages called tweets. A tweet is a 140 characters long message that is rarely self -cont, hence additional information are necess ary to allow better readability of the tweet. This new task has attracted a great deal of attention recently. Given a tweet, the aim of tweet contextualization is to produce an informative and coherent paragraph, called a context, from a set of documents in response to topics treated by the tweet. In this paper, we propose a new approach of Tweet Contextualization based on combining automatic summarization techniques and sentence aggregation. The main idea of our proposed method is to select relevant, info rmative and semantically related sentences that best describe themes expressed by the tweet, and then build a concise context.

Sujay Muramalla, Ragaad AlTarawneh, Shah Rukh Humayoun, Ricarda Moses, Sven Panis, Achim Ebert

Space-filling techniques have been used in the information visualization field as an alternative to the conventional node-link layouts for intuitively showing large hierarchies in less space. Different space filling layouts have been designed, developed and evaluated; however, much less effort have been made to look into how layout can impact user task performance on hierarchical data structures . In this paper, we focus on the impact of layout on user task performance by conducting eval uation studies for two common space-filling layout structures, the Sunburst (radial) layout and the Icicle (rectangular) layout. In our studies, users performed eight search -based tasks on files and directories in the resulting visualizations, first in a controlled environment and subsequently in an online environment. We focused on deriving user performance metrics with regard to effectiveness, efficiency, and user acceptance. Results demonstrate a mixed view of task performance and preference with both la youts, e.g., users performed better with the Icicle layout while they preferred the Sunburst layout for visual aesthetics. We further analyzed the impact of layout on the performance dynamics in terms of response times and accuracy using event history analysis (EHA) in the control study setting. The EHA results revealed clear differences in response tendencies even though no differences existed in mean response times for most of the tasks. It also clearly showed that participants performed more efficiently with the directory comparison tasks than the file comparison tasks. Overall, through these studies we were able to derive causal relationships between the layout and the user’s task performance while interacting with hierarchical data structures.

Hardy Pundt

Spatial decision making often requires the consideration of huge datasets fro m a great variety of sectors . For the achievement of decision that are accepted by as many actors as possible it is indispensable to consider all relevant fields, and contexts. However, if the goal of a project is ill defined or broadly scoped, it can be h ard to identify all relevant actors and overview whether their different goals, perceptions and ideas of how a place, a landscape, a village or city should develop in the future, can be integrated. Actors recognize problems necessarily within their specifi c context. The idea of a holistic approach to decision making is to consider possibly all relevant contexts, in which a spatial problem is embedded. This should lead to qualitatively high and sustainable decisions because the ignorance of specific contextual information can lead to unsatisfying, in the worst case harmful results . The problem as such is not new, but this paper argues not from a perspective of human communication. It raises the question, whether applications can support a holistic approach in spatial decision making by extending decision systems with functionalities to integrate context-information automatically.

Oksana Arnold, Sebastian Drefahl, Jun Fujima, Klaus P. Jantke, Christoph Vogler

In contemporary information and communication technolo gies, there is an urgent need for transforming tools into assistant systems. Humans do not need more digital tools that require learning how to wield them, but digital assistants guiding them to unforeseeably valuable results – an effect named serendipity. This applies particularly when dealing with wicked prob lems which change over time when being tackled. Data analysis, visualization, and exploration is a characteristic domain of this type , particularly when open data are in focus, because the analysts have no background knowledge about the origin of these open data. The paper demonstrates the t ransformation of a tool for data analysis into an intelligent adaptive assistant. The transformation is based on the exploitation of concepts, methods, and technologies from disciplines such as meme media technology, natural language processing, and theory of mind modeling and induction. In comparison to earlier approaches to computational theory of mind induction, the present one relies on dynamically generated spaces of hypotheses. A rigorous mathematical proof demonstrates the superiority of the novel reasoning technology. A case study in business intelligence serves as proof of concept.

Ray R. Hashemi, Azita A. Bahrami, Jeffrey A. Young, Nicholas R. Tyler, Jay Y. S. Hodgson

Climate changes around a large body of water have an intertwined relationship with the salinity of the water and diatom algae growing within it. One may use the diatom algae fossils obtained from bottom of an inland lake to conclude the historical climate c hanges around the lake and by extension the historical salinity of the water. The discovery of the historical quantified salinity of inland lakes is extremely important to understanding climate change, carbon dioxide levels, and global warming. In this research effort, the past salinity level s for Santa Fe Lake located in New Mexico, USA, were discovered by mining t he data of diatom algae fossils . Modified Rough Sets as the first component of the proposed hybrid system were used to establish the relationships between diatom algae data, expressed in linguistic values, and the climate changes. The established relationships were extended to embrace the linguistic values of water salinity. The outcome was a set of fuzzy patterns. Fuzzy Logic as the second component of the proposed hybrid system was employed to: (i) provide the membership functions for the different linguistic values of the salinity and (ii) produce a crisp value for the salinity of the water related to each slice of diatom fossil using the crisp values of algae abundance indices in each slice. The validity of the findings was tested which revealed 72% of accuracy for the produced results.

Samuel Mann Capable NZ, Otago Polytechnic, Dunedin Researcher, New Zealand

The premise of Computing Education for Sustainability ( CEfS) is examined. CEfS is described as a leverage discipline, where the handprint is much larger than the footprint. The potential of this leverage is described and the development of the field explored. Unfortunately CEfS is found not to be making sufficient impact in terms of a contribution at scale to system change actions resulting in restorative socio-ecological transformation. A transformation mindset is described that provides a lens for considering the role of CEfS and what might be done about it. Three inspirations are described - a case study of a learner with an ambitious change aspiration, a values -driven business, and an alternative approach to education: work-based pro fessional practice education. These lead to consideration of implications, which while not exhaustive, are intended to provoke debate about the nature of computing education for sustainability.

Reza Kiani Mavi, Craig Standing.

Government regulations require businesses to improve their processes and products/services in a green and sustainable manner. For being environmentally friendly, businesses should invest more on eco-innovation practices. Firms eco -innovate to promote eco -efficiency and sustainability. This paper evaluates the eco-innovation performance of Organisation for Economic Co -operation and Development (OECD) countries with data envelopment analysis (DEA). Output oriented CCR (Charnes, Cooper and Rhodes) is applied because of more desirability of outputs for decision makers. Data were gathered from the World bank database and global innovation index report. Findings show that for most OECD countries, energy use and ecological sustainability are more important than other inputs and outputs for enhancing eco-innovation.

Pavel Tarasov, Hitesh Tewari

Voting systems have been around for hundreds of years and despite different views on their integrity, have always been deemed secure with some fundamental security and anonymity principles. Numerous electronic systems have been proposed and implemented but some suspicion has been raised regarding the integrity of elections due to detected security vulnerabilities within these systems. Electronic voting, to be successful, requires a more transparent and secure approach, than is offered by current protocols. The approach presented in this paper involves a protocol developed on blockchain technology. The underlying technology used in the voting system is a payment scheme, which offers anonymity of transactions, a trait not seen in blockchain protocols to date. The proposed protocol offers anonymity of voter transactions, while keeping the transactions private, and the election transparent and secure. The underlying payment protocol has not been modified in any way, the voting protocol merely offers an alternative use case.

Hanene Rouabeh, Chokri Abdelmoula, Mohamed Masmoudi

One of the most important and challengi ng tasks in the image processing field is color segmentation . In this paper, we propose a red color segmentation algorithm which is developed to be used as a mandatory task of a complete vision based intelligent speed limit road sign recognition system. This type of sign is characterized by a red border. For this reason the segmentation remains important in the detection task. A simple and accurate technique was proposed which presents a modified and improved thresholding based method that uses the Red, Green and Blue color space components . In order to improve the robustness and efficiency, a pretreatment was proposed in our work to be applied on images before thresholding. This pretreatment is divided into two steps; the first one is c lassification. The ai m is to classify images according to different illumination condition s. The second one consists in color adjustment and correction. These two algorithms were introduced to solve problems caused firstly by the use of same thresholding values for different i mages, and secondly by the sensibility of colors to lightening conditions variation. The comparison with existent methods has shown robustness and accuracy mainly for images of different day times and for faded and blurred signs . In addition to that low c omputation time is achieved. The software implementation of the developed segmentation algorithm using MATLAB tool is discussed in this paper, as well as the simulation results of the VHDL Circuit using ModelSim tool. Computational time reduction, low complexity and low resource utilization have shown the effectiveness of our approach.

Duarte Pousa, José Rufino

System Virtualization has become a fundamental IT tool, whether it is type -2/hosted virtualization, mostly exploited by end -users in their personal computers, or type -1/bare metal, well established in IT departments and thoroughly used in modern datacenters as the very foundation of clou d computing. Though bare metal virtualization is meant to be deployed on server -grade hardware (for performance, stability and reliability reasons), properly configured desktop -class systems or workstations are often used as virtualization servers, due to their attractive performance/cost ratio. This paper presents the results of a study conducted on commodity virtualization servers , aiming to assess the performance of a representative set of the type -1 platforms mostly in use today: VMware ESXi, Citrix Xen Server, Microsoft Hyper -V, oVirt and Proxmox. Hypervisor performance is indirectly measured through synthetic benchmark s performed on Windows 10 LTSB and Linux Ubuntu Server 16.04 guests: PassMark for Windows, UnixBench for Linux, and the cross -platform Flexible I/O Tester and iPerf 3 benchmarks. The evaluation results may be used to guide the choice of the best type-1 platform (performance-wise), depending on the predominant guest OS, the performance patterns (CPU- bound, IO-bound, or balanced) of that OS, its storage type (local/remote) and the required network-level performance.

Pedro Isaías

Editorial preface for Volume 12, Issue 2 of the IADIS International Journal on Computer Science and Information Systems (IJCSIS). This issue brings together peer-reviewed original research contributions covering the wide spectrum of Information Systems, Artificial Intelligence, Software Engineering, and Digital Transformation.