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A machine learning approach for simultaneous demapping of QAM and APSK constellations
No full textAs telecommunication systems evolve to meet increasing demands, integrating deep neural networks (DNNs) has shown promise in enhancing performance. However, the trade-off between accuracy and flexibility remains challenging when replacing traditional receivers with DNNs. This paper introduces a novel probabilistic framework that allows a single DNN demapper to demap multiple QAM and APSK constellations simultaneously. We also demonstrate that our framework allows exploiting hierarchical relationships in families of constellations. The consequence is that we need fewer neural network outputs to encode the same function without an increase in Bit Error Rate (BER). Our simulation results confirm that our approach approaches the optimal demodulation error bound under an Additive White Gaussian Noise (AWGN) channel for multiple constellations. Thereby, we address multiple important issues in making DNNs flexible enough for practical use as receivers
Exploring relationships among topics in neuroscience literature using augmented reality visualization
Get PDFNeuroscience researchers frequently consult scholarly articles to guide their experimental inquiries, primarily aiming to identify potential new experiments. To determine viable experiments, neuroscientists must understand established relationships among mental functions, brain regions, and neurological diseases. Since neuroscience experiments to verify specific relationships are costly and time-consuming, it is crucial to accurately identify those with the most potential to advance knowledge. For instance, a relationship mentioned in only a few studies might indicate a lack of experimental evidence rather than a non-existent causal link. We propose that using Augmented Reality (AR) to visualize data from neuroscience literature can help researchers identify existing or potentially fruitful relationships for further exploration. To support this assertion, we conducted three user-centered design studies using 3D AR visualizations tailored for different exploratory tasks. Our approach involved developing an immersive AR system named "DatAR," which formed the basis of our experimental studies. In the first study, we focused on identifying potential tasks for exploring neuroscience literature and determining suitable visual supports. We introduced an early version of DatAR to eight neuroscience students, who were tasked with identifying specific relationships. After completing the task, participants could explore the implemented functionalities and visualizations. Subsequent interviews validated the relationship-finding feature and the effectiveness of the visual representations. We later enhanced the system to display sentences and references linked to a specific disease and brain region relationship, supporting searches from a disease to related regions and vice versa. Experts in literature research evaluated this functionality, confirming that the DatAR prototype's relationship-finding feature was meaningful, understandable, and that the 3D visualizations aided in comprehending neuroscience topics. This provided initial evidence that AR visualizations could facilitate the identification of relationships conducive to fruitful experiments. Another observation from the initial studies was the frequent need among neuroscientists to compare how two diseases affect the same brain regions. In response, our third study explored how AR visualizations could assist in comparing affected brain regions. We provided 3D models emphasizing the regions impacted by different diseases, enhancing participants' understanding and enabling them to explore patterns and relationships more effectively. This approach allowed researchers to identify a small number of relevant papers for in-depth study without the need to review extensive literature. In subsequent evaluations, we assessed each developed functionality as a separate widget. The final study explored how these functionalities, when combined, could support neuroscience research. We engaged three neuroscientists to define representative tasks and scenarios that utilized most of the developed widgets in a coordinated manner. The results demonstrated that this ensemble of widgets was particularly beneficial for new researchers in neuroscience, helping them understand complex relationships between brain-related topics. The widgets supported each other in visualizing and verifying results, proving to be invaluable. Overall, our studies laid a solid foundation for understanding how AR can effectively elucidate complex relationships among neuroscience topics, demonstrating that an immersive AR environment can effectively display topics and their interconnections, thereby facilitating the exploration of neuroscience literature
ForametCeTera, a novel CT scan dataset to expedite classification research of (non-)foraminifera
Get PDFThis paper introduces ForametCeTera, a pioneering dataset designed to address the challenges associated with automating the analysis of benthic foraminifera in sediment cores. Foraminifera are sensitive sentinels of environmental change and are a crucial component of carbonate-denominated ecosystems, such as coral reefs. Studying their prevalence and characteristics is imperative in understanding climate change. However, analysis of foraminifera contained in core samples currently requires washing, sieving and manual quantification. These methods are thus time-consuming and require trained experts. To overcome these limitations, we propose an alternative workflow utilizing 3D X-ray computational tomography (CT) for fully automated analysis, saving time and resources. Despite recent advancements in automation, a crucial lack of methods persists for segmenting and classifying individual foraminifera from 3D scans. In response, we present ForametCeTera, a diverse dataset featuring 436 3D CT scans of individual foraminifera and non-foraminiferan material following a high-throughput scanning workflow. ForametCeTera serves as a foundational resource for generating synthetic digital core samples, facilitating the development of segmentation and classification methods of entire core sample CT scans
Algoritme rekent af met lange wachttijden: "Toeristen minder lang in de rij"-AT5-4-8-2024
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Communication challenges between clients and producers of immersive media applications: Can social XR help?
Get PDFExtended Reality (XR) has emerged as a transformative and immersive technology with versatile applications in content creation and consumption. As XR gains popularity, companies eager to adopt it often possess a surface-level understanding, investing significant resources without effectively addressing the genuine needs of end-users. This study explores the current workflows of XR production companies, and the potential of social XR in mitigating challenges throughout the XR production workflow. We present the outcomes of three respective focus group workshops conducted with three XR production companies and their experts (N=17). The results indicate that at every stage of the production, namely pre-production, production, post-production, and post-release, there are communication challenges between producers and clients, as well as different production and post-production specialists. We discuss various aspects of XR concerning the problem and propose novel opportunities offered by social XR to ameliorate those challenges, improving communication and making development more agile
Associative electron detachment in sprites
Get PDFThe balance of processes affecting electron density drives the dynamics of upper-atmospheric electrical events, such as sprites. We examine the detachment of electrons from negatively charged atomic oxygen (O−) via collisions with neutral molecular nitrogen (N2) leading to the formation of nitrous oxide (N2O). Past research posited that this process, even without significant vibrational excitation of N2, strongly impacts the dynamics of sprites. We introduce updated rate coefficients derived from recent experimental measurements which suggest a negligible influence of this reaction on sprite dynamics. Given that previous rates were incompatible with the observed decay of the light emissions from sprite glows, our findings support that glows actually result from electron depletion in sprite columns
