Baseline Methods for Automated Fictional Ideation

The invention of fictional ideas (ideation) is often a central process in the creative production of artefacts such as poems, music and paintings, but has barely been studied in the Computational Creativity community. We present here three baseline approaches for automated fictional ideation, using methods which invert and alter facts from the ConceptNet and ReVerb databases, and perform bisociative discovery. For each method, we present a curation analysis, by calculating the proportion of ideas which pass a typicality evaluation. We further evaluate one ideation approach through a crowd- sourcing experiment in which participants were asked to rank ideas. The results from this study, and the baseline methods and methodologies presented here, constitute a firm basis on which to build more sophisticated models for automated ideation with evaluative capacity

Conceptual Representations for Computational Concept Creation

Computational creativity seeks to understand computational mechanisms that can be characterized as creative. The creation of new concepts is a central challenge for any creative system. In this article, we outline different approaches to computational concept creation and then review conceptual representations relevant to concept creation, and therefore to computational creativity. The conceptual representations are organized in accordance with two important perspectives on the distinctions between them. One distinction is between symbolic, spatial and connectionist representations. The other is between descriptive and procedural representations. Additionally, conceptual representations used in particular creative domains, such as language, music, image and emotion, are reviewed separately. For every representation reviewed, we cover the inference it affords, the computational means of building it, and its application in concept creation.Peer reviewe

Clinical validity assessment of genes frequently tested on intellectual disability/autism sequencing panels.

[en] PURPOSE: Neurodevelopmental disorders (NDDs), such as intellectual disability (ID) and autism spectrum disorder (ASD), exhibit genetic and phenotypic heterogeneity, making them difficult to differentiate without a molecular diagnosis. The Clinical Genome Resource Intellectual Disability/Autism Gene Curation Expert Panel (GCEP) uses systematic curation to distinguish ID/ASD genes that are appropriate for clinical testing (ie, with substantial evidence supporting their relationship to disease) from those that are not. METHODS: Using the Clinical Genome Resource gene-disease validity curation framework, the ID/Autism GCEP classified genes frequently included on clinical ID/ASD testing panels as Definitive, Strong, Moderate, Limited, Disputed, Refuted, or No Known Disease Relationship. RESULTS: As of September 2021, 156 gene-disease pairs have been evaluated. Although most (75%) were determined to have definitive roles in NDDs, 22 (14%) genes evaluated had either Limited or Disputed evidence. Such genes are currently not recommended for use in clinical testing owing to the limited ability to assess the effect of identified variants. CONCLUSION: Our understanding of gene-disease relationships evolves over time; new relationships are discovered and previously-held conclusions may be questioned. Without periodic re-examination, inaccurate gene-disease claims may be perpetuated. The ID/Autism GCEP will continue to evaluate these claims to improve diagnosis and clinical care for NDDs

Experience with Multi-Attribute Decision Models in Decision Support on Genetically Modified Organisms

In the paper we present applications of a qualitative multi-attribute modelling method DEX for decision support about the introduction and use of geneticallymodified organisms (GMO) for food and feed. In three 5th and 6th Framework Programme European projects, we have developed a number of models, of which we present three: the »Grignon« model for the assessment of ecological and economic impacts of GMO, ESQI model for the assessment of soil quality, and SMAC model for the assessment of co-existence of conventional and GMO maize. We also mention a decision support system developed within the project Co-Extra. In the second part, we assess the achieved results and describe our lessons learned during the model development

Modelling impacts of cropping systems: Demands and solutions for DEX methodology

Decision modelling of diverse groups of problems makes different requirements to the modelling methodologies and software. We present an actual decision problem and the required characteristics of corresponding decision models. The problem is from agronomy and addresses the ecological and economic impacts of cropping systems, with the focus on the differences between cropping systems with conventional crops and the ones with genetically modified crops. We describe the extensions of an existing DEX qualitative multi-attribute modelling methodology, which were made to cope with the challenges of the problem. The extensions address general hierarchical structures, probabilistic utility functions and numerical values of basic attributes. A new, freely available software tool called proDEX was implemented to support the extended methodology. In this paper we describe the problem of cropping system assessment, propose methodological extensions to DEX, and present the implementation of proDEX.

Analytical DSS module : how to support decisions in the analytical lab

National audienc

PROGRAM APLIKASI ENKRIPSI DAN DEKRIPSI SMS PADA PONSEL BERBASIS ANDROID DENGAN ALGORITMA DES

Short Message Service (SMS) merupakan sebuah revolusi teknologi komunikasi yang sangat popular. Dengan menggunakan SMS seseorang dapat saling bertukar pesan dengan orang lain. Namun,dengan adanya masalah penyadapan SMS, seseorangsudah tidaklagi mempunyai hak privasi. Sehingga akan dikembangkan  sebuahprogram aplikasi padatelepon selularberbasis Android yangakan merubahpesan SMS menjadi kode-kode agar isi informasi dari SMS tersebut tidak diketahui orang lain. Dalam pengiriman SMS, aplikasi ini akan mengenkripsi pesan ke dalam bentuk kode dengan key yang diinputkan oleh pengirim yang kemudian pesan kode tersebut dikirm ke nomor tujuan. Dalam penerimaan SMS, aplikasi ini akan mendekripsi pesan kode tersebut ke dalam bentuk pesan asli dengan menggunakan key yang samadengankey pengirim. Aplikasi ini dapat dimanfaatkan olehseseorang yang menggunakan telepon selular berbasis Android untuk mengirimkan suatu pesan penting kepada oranglain tanpa takut diketahuioleh orang yang tidak berwenang. Metode yang digunakanaplikasi ini dalam mengenkripsi dan mendekripsi pesan adalah metode blok cipheralgoritma DES dan implementasinya menggunakanbahasa pemrograman Java dengan platform mobile Android.

The co-extra decision support system : a model-based integration of project results

National audienc