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This article presents a research outline on the use of microlearning applications to develop digital competencies in Small and Medium-sized Enter-prises (SMEs). The digital transformation of businesses has become essential for their survival, and SMEs need to develop digital competencies (DC) to remain competitive in the market. Microlearning (ML), a form of learning that involves small, bite-sized learning modules, has been gaining popularity in recent years as a way to efficiently and effectively develop skills. Through a semi-systematic literature review approach, our study examines prevalent knowledge in the area of ML and DC and discusses interrelations. As a result, we propose a research roadmap consisting of six research questions targeting four dimensions of ML for DC development in SMEs: 1) context, 2) formats, 3) reward system, and 4) complexity level.
Digital transformation initiatives in small and medium-sized enterprises (SME) are often hampered by individual practitioners' perceptions of information and communication technology (ICT). This research employs an educational escape room (ER) game for an intervention towards informed decision-making on ICT adoption in SMEs. ER design and implementation are elaborated and consequently tested with SME practitioners, all embedded in an action-design study based on a qualitative research methodology. The result highlights a trade-off between creating immersive game experiences and achieving learning objectives. Still, the outcome implies an impact on players' perception of ICT integrated in the ER. The findings contribute to the emerging field of serious games for learning and shed light on the potential of game-based interventions for SMEs.
This paper presents a study on the feasibility of using large language models (LLM) for coding with low-resource and domain-specific programming languages that typically lack the amount of data required for effective LLM processing techniques. This study focuses on the econometric scripting language named hansl of the open-source software gretl and employs a proprietary LLM based on GPT-3.5. Our findings suggest that LLMs can be a useful tool for writing, understanding, improving, and documenting gretl code, which includes generating descriptive docstrings for functions and providing precise explanations for abstract and poorly documented econometric code. While the LLM showcased promoting docstring-to-code translation capability, we also identify some limitations, such as its inability to improve certain sections of code and to write accurate unit tests. This study is a step towards leveraging the power of LLMs to facilitate software development in low-resource programming languages and ultimately to lower barriers to entry for their adoption.
Ubiquitous Music is an interdisciplinary research area that combines methodologies from music, computer science, education, creativity studies, human sciences and engineering.
The Ubiumus 2023 symposium, held at Ulster University and North West Regional College in Derry~Londonderry, Northern Ireland, included contributions on the following topics:
Rapid Prototyping and Live Environments
Ecological Approaches to Ubiquitous Music
Ubiquitous Music Creative Practices, Tools and Influences
The symposium also included a number of artistic contributions and workshops, which are also discussed in the proceedings volume. A number of events (including all paper presentations, an invited lecture, a panel discussion, and a keynote and associated performance) were also documented via video, with a link available in this Proceedings volume.
This Paper proposes a novel method for the blind detection of image pre-processing techniques by means of statistical pattern recognition in image forensics. The technique is intended to detect sensor intrinsic pre-processing steps as well as manually applied filters. We have exemplary chosen 6 pre-processing filters with different parameter settings. The concept utilizes 29 image features which are supposed to allow for a reliable model creation during supervised learning. The evaluation of the trained models indicates average accuracies between 82.50 and 94.53%. The investigation of image data from 8 sensors leads to the detection of credible pre-processing filters. Those results adumbrate that our method might be suitable to prove the authenticity of the data origin and the integrity of image data based on the detected preprocessing techniques. The preliminary evaluation for manually applied filters yields recognition accuracies between 39.09% (14 classes) and 53.33% (7 classes).
We investigate micrometer-sized flat droplets consisting of an isotropic core surrounded by a nematic rim in freely suspended smectic A liquid-crystal films. In contrast to purely isotropic droplets which are characterized by a sharp edge and no long-range interactions, the nematic fringe introduces a continuous film thickness change resulting in long-range mutual attraction of droplets. The coalescence scenario is divided in two phases. The first one consists in the fusion of the nematic regions. The second phase involves the dissolution of a thin nematic film between the two isotropic cores. The latter has many similarities with the rupture of thin liquid films between droplets coalescing in an immiscible viscous liquid.
Coalescence of biphasic droplets in free-standing smectic films is controlled in part by the rupture of a thin nematic membrane separating the isotropic droplet cores.
Sensing is nowadays an accepted application of phononic crystals with chemical and biosensors for liquid analytes being the perhaps most promising ones. A liquid-filled defect is introduced that turns into a resonant cavity. Similar to the well-known resonant sensors sensitivity can be increased with higher operating frequencies. We introduce a Sandwiched Phononic Crystal (SPC), which applies a resonant cavity located between two stacked layers on top of a SAW device. Key challenges are coupling of surface acoustic wave into the liquid cavities and avoiding scattering of the guided waves into the bulk of the sensor chip.
Phononic crystals (PnC) with a specifically designed liquid-filled defect have been recently introduced as a novel sensor platform (Lucklum et al. in Sens Actuators B Chem 171–172:271–277, 2012). Sensors based on this principle feature a band gap covering the typical input span of the measurand as well as a narrow transmission peak within the band gap where the frequency of maximum transmission is governed by the measurand. This approach has been applied for determination of volumetric properties of liquids (Lucklum et al. in Sens Actuators B Chem 171–172:271–277, 2012; Oseev et al. in Sens Actuators B Chem 189:208–212, 2013; Lucklum and Li in Meas Sci Technol 20(12):124014, 2009) and has demonstrated attractive sensitivity. One way to improve sensitivity requires higher probing frequencies in the range of 100 MHz and above. In this range surface acoustic wave (SAW) devices are an established basis for sensors. We have performed first tests towards a PnC microsensors (Lucklum et al. in Towards a SAW based phononic crystal sensor platform. In: 2013 Joint European frequency and time forum and international frequency control symposium (EFTF/IFC), pp 69–72, 2013). The respective feature size of the PnC SAW sensor has dimensions in the range of 10 µm and below. Whereas those dimensions are state of the art for common MEMS materials, etching of holes and cavities in piezoelectric materials that have an aspect ratio diameter/depth is still challenging. In this contribution we describe an improved technological process able to realize considerably deep and uniform holes in a SAW substrate.