International Journal of Arts and Technology (6 papers in press)
Investigating the Relationship between Form and Content in Interactive Graphic with a Semiotic Approach
by Sara Jahangiri, Seyyed Nezamodin Emamifar
Abstract: In this research, the relationship between form and content in interactive graphic arts is examined from the semiotics point of view. This research has studied the importance of the relationship between form and content in the formation of interactive graphic in semiotics and it has also dealt with the work of the relationship between form and content in the formation of virtual reality and the position of audience in interactive graphics and the recognition of the passwords and the interpretation of the signs by which the content is determined. The research methodology is based on the descriptive-analytical nature and data collection which is done through combined method (library and field) and the number of samples are 6 images. The data analysis method has also been qualitative approach. In this article, after mentioning the fundamental and substantive topics of semiotics, the author has focused on these topics by reading six interactive graphic works and has attempted to analyze semiotics together with answering the research questions and hypotheses. The results of examining the samples show that in most of them, the relationship between form and content in interactive graphics from the semiotics point of view is to create visual shock to the audience. And for inducing the concept, the dominant mode is also the use of indexing elements.
Keywords: Form; Content; Environmental Graphics; Semantics; Interactive Graphics.
Are ICT good partners for the development of creativity? A systematic review of literature
by Ludwig Markbent Angarita, Andrés Chiappe
Abstract: Creativity is considered one of the key skills of the 21st century. Likewise, information and communication technologies (ICT) have been identified as a constant presence in contemporary education, where there is the persistent challenge of developing creative thinking in children and young people who will live and perform in a highly globalised, interconnected, changing and uncertain social and cultural context. To better understand the relationship between the educational use of ICT and the development of creativity, a systematic literature review was carried out on 100 published studies with this subject. The results highlight on the one hand, the coexistence of three different conceptualisations on creativity and on the other hand, the identification of both contributions and barriers of ICT to the development of creative thinking that have more to do with cultural, attitudinal and organisational issues about their educational use than with the very nature of ICT.
Keywords: collaborative work; creativity; creative thinking; education; information and communication technologies; ICT; innovation; knowledge; educational skills; 21st century education; systematic literature review.
Situational perceived competence and choice when using digital technology in an inquiry-based learning setting in arts and crafts
by Manuela Heindl
Abstract: Although there is evidence of an improvement in pupil's learning achievements in inquiry-based learning sessions compared to traditional lessons, the influence of technology, especially in primary schools, has not yet been analysed yet. The question is, whether inquiry-based learning with digital technology leads to better outcomes, which will be indirectly measured through the final product and the pupil's perceived and choice. The latter is part of the intrinsic motivation, which can also improve pupil's scores according to Deci and Ryan. The treatment group used digital technology to solve a scientific architectural problem in the creative subject 'arts and crafts' and the control group used worksheets instead. The pupils were given the standardised intrinsic motivation inventory questionnaire by Deci and Ryan. The Whitney-Mann U-test concluded that the treatment group felt more competent (U = 4,149, p = 0.006) than the control group and reported a desired teaching effect (d = 0.419) but there was no significance for pupil's perceived choice (U = 5,019, p = 0.514). There was a weak but positive correlation between 207 pupil's successful product and their situational perceived competence (rs = 0.299, p = 0.001), but no significance for perceived choice (rs = 0.133, p = 0.057).
Keywords: inquiry-based learning; arts; primary school; motivation.
Research on invulnerability of scale-free network with a unified method
by Kaiju Li, Hao Wang
Abstract: Research on the invulnerability of scale-free network has outstanding benefit on building robust social, biological and technological networks in real world. Intuitively, prior studies attempt to investigate this topic under different conditions, including node/edge attack with or without cost, and get many valuable conclusions. However, current methods just evaluate the invulnerability from a single viewpoint, and lack a comprehensive description of this performance. Therefore, this paper proposes a unified framework to explore the invulnerability of scale-free network. Specifically, by exploring the transformation relations among node, edge and attack cost, we define a weight parameter t to unify the four cases, e.g., node/edge attack with or without cost. By this means, we can analyse the invulnerability from a comprehensive perspective rather than a single perspective. Furthermore, we re-analyse the invulnerability of scale-free network using our unified method and investigate the relationships among current research conclusions. Theoretical analysis and experimental results show that current conclusions are the cases corresponding to the specific values of t, and our method obtains other useful invulnerability conclusions with current methods.
Keywords: scale-free network; invulnerability; node attack; edge attack; weight parameter; unified analysis.
QSJoin: a new string similarity join method based on Q-sample and statistical features
by Xiaoxia Wang, Decai Sun, Bo Wu, Puzhao Ji
Abstract: Similarity joins is an essential operation in big data analytics, such as data integration and data cleaning. In this paper, we propose a new algorithm, called QSJoin, to support efficient string similarity join by reducing the shuffle cost and transmission cost in MapReduce. Our algorithm employs a filter-verify framework. In filtration, a new signature scheme based on q-sample is adopted to decrease the number of generated signatures, and then a large number of dissimilar pairs are discarded with Standard-Match filter. In verification, a multi-vector filter scheme is adopted to eliminate more dissimilar pairs with statistical features, and then the final true pairs is extracted by the verification of candidate pairs with length-aware verification method. Experimental result on real-world datasets shows that our algorithm achieves high performance and outperforms state-of-the-art approaches.
Keywords: string similarity join; MapReduce; Q-sample; statistical feature; data integration.
The art of domain classification and recognition for text conversation using support vector classifier
by Sandeep Rathor, R.S. Jadon
Abstract: This paper presents an art for recognition of text conversation into multiple domain categories using SVC. The whole process of recognition includes diverse components as: lexical analysis, feature extraction, features normalisation, feature reduction and finally recognition. Useful words are extracted using lexical analysis from the input text paragraph and transformed it into a binary matrix for further processing through feature extraction. Feature normalisation is used to normalise the values of binary matrices while feature reduction is done through principal component analysis to extract the important features from the feature vector and now it is passed to different configurations of SVM, then the best one is selected for the final process of classification and recognition. The domain's categories are defined on the basis of various real life situations and conversation to train the system like education and research, personal, patriotism, terrorism, medical, religious, sports, and business. The experimental results demonstrate that the proposed approach works effectively with about 75% accuracy.
Keywords: domain classification; domain recognition; conversation findings; machine learning.