Compressed Sensing based Dynamic PSD Map Construction in Cognitive Radio Networks

In the context of spectrum sensing in cognitive radio networks, collaborative spectrum sensing has been proposed as a way to overcome multipath and shadowing, and hence increasing the reliability of the sensing. Due to the high amount of information to be transmitted, a dynamic compressive sensing approach is proposed to map the PSD estimate to a sparse domain which is then transmitted to the fusion center. In this regard, CRs send a compressed version of their estimated PSD to the fusion center, whose job is to reconstruct the PSD estimates of the CRs, fuse them, and make a global decision on the availability of the spectrum in space and frequency domains at a given time. The proposed compressive sensing based method considers the dynamic nature of the PSD map, and uses this dynamicity in order to decrease the amount of data needed to be transmitted between CR sensors’ and the fusion center. By using the proposed method, an acceptable PSD map for cognitive radio purposes can be achieved by only 20 % of full data transmission between sensors and master node. Also, simulation results show the robustness of the proposed method against the channel variations, diverse compression ratios and processing times in comparison with static methods

Search Bias Quantification: Investigating Political Bias in Social Media and Web Search

Users frequently use search systems on the Web as well as online social media to learn about ongoing events and public opinion on personalities. Prior studies have shown that the top-ranked results returned by these search engines can shape user opinion about the topic (e.g., event or person) being searched. In case of polarizing topics like politics, where multiple competing perspectives exist, the political bias in the top search results can play a significant role in shaping public opinion towards (or away from) certain perspectives. Given the considerable impact that search bias can have on the user, we propose a generalizable search bias quantification framework that not only measures the political bias in ranked list output by the search system but also decouples the bias introduced by the different sources—input data and ranking system. We apply our framework to study the political bias in searches related to 2016 US Presidential primaries in Twitter social media search and find that both input data and ranking system matter in determining the final search output bias seen by the users. And finally, we use the framework to compare the relative bias for two popular search systems—Twitter social media search and Google web search—for queries related to politicians and political events. We end by discussing some potential solutions to signal the bias in the search results to make the users more aware of them.publishe

Differential Transform Method for Nonlinear Parabolic-hyperbolic Partial Differential Equations

In the present paper an analytic solution of non-linear parabolic-hyperbolic equations is deduced with the help of the powerful differential transform method (DTM). To illustrate the capability and efficiency of the method four examples for different cases of the equation are solved. The method can easily be applied to many problems and is capable of reducing the size of computational work

Persona transparency: analyzing the impact of explanations on perceptions of data-driven personas

Computational techniques are becoming more common in persona development. However, users of personas may question the information in persona profiles because they are unsure of how it was created. This problem is especially vexing for data-driven personas because their creation is an opaque algorithmic process. In this research, we analyze the effect of increased transparency–i.e., explanations of how the information in data-driven personas was produced–on user perceptions. We find that higher transparency through these explanations increases the perceived completeness and clarity of the personas. Contrary to our hypothesis, the perceived credibility of the personas decreases with the increased transparency, possibly due to the technical complexity of the persona profiles disrupting the facade of the personas being real people. This finding suggests that explaining the algorithmic process of data-driven persona creation involves a “transparency trade-off”. We also find that the gender of the persona affects the perceptions, with transparency increasing perceived completeness and empathy of the female persona, but not for the male persona. Therefore, transparency may specifically assist in the acceptance of female personas. We provide practical implication for persona creators regarding transparency in persona profiles.info:eu-repo/semantics/acceptedVersio

Dynamics of the topological structures in inhomogeneous media

We present a general review of the dynamics of topological solitons in 1 and 2 dimensions and then discuss some recent work on the scattering of various solitonic objects (such as kinks and breathers etc) on potential obstructions.Comment: based on the talk given by W.J. Zakrzewski at QTS5. To appear in the Proceedings in a special issue of Journal of Physics

Self-supervised video pretraining yields human-aligned visual representations

Humans learn powerful representations of objects and scenes by observing how they evolve over time. Yet, outside of specific tasks that require explicit temporal understanding, static image pretraining remains the dominant paradigm for learning visual foundation models. We question this mismatch, and ask whether video pretraining can yield visual representations that bear the hallmarks of human perception: generalisation across tasks, robustness to perturbations, and consistency with human judgements. To that end we propose a novel procedure for curating videos, and develop a contrastive framework which learns from the complex transformations therein. This simple paradigm for distilling knowledge from videos, called VITO, yields general representations that far outperform prior video pretraining methods on image understanding tasks, and image pretraining methods on video understanding tasks. Moreover, VITO representations are significantly more robust to natural and synthetic deformations than image-, video-, and adversarially-trained ones. Finally, VITO's predictions are strongly aligned with human judgements, surpassing models that were specifically trained for that purpose. Together, these results suggest that video pretraining could be a simple way of learning unified, robust, and human-aligned representations of the visual world.Comment: Technical repor

Personalized Service Creation by Non-technical Users in the Homecare Domain

AbstractOne of the conditions for the successful introduction of ICT-based homecare services is to allow non-technical persons such as home nurses to personalize these services. We refer to this process of homecare service personalization as service tailoring. Service tailoring can be done by configuring and composing previously developed and deployed service building blocks. In this paper, we describe an approach that employs predefined information of care-receivers, called user profile, to hide most of the technical details from care-givers who do the service tailoring. First, we define the information to be included in a user profile and patterns that represent composition structures corresponding to common homecare tasks experienced in homecare. Then, we define how the service tailoring process can exploit information contained in the predefined user profiles. After that, we illustrate the approach with a tailoring scenario

Tetracycline aptamer-controlled regulation of pre-mRNA splicing in yeast

Splicing of pre-mRNA is a critical step in mRNA maturation and disturbances cause several genetic disorders. We apply the synthetic tetracycline (tc)-binding riboswitch to establish a gene expression system for conditional tc-dependent control of pre-mRNA splicing in yeast. Efficient regulation is obtained when the aptamer is inserted close to the 5′splice site (SS) with the consensus sequence of the SS located within the aptamer stem. Structural probing indicates limited spontaneous cleavage within this stem in the absence of the ligand. Addition of tc leads to tightening of the stem and the whole aptamer structure which probably prevents recognition of the 5′SS. Combination of more then one aptamer-regulated intron increases the extent of regulation leading to highly efficient conditional gene expression systems. Our findings highlight the potential of direct RNA–ligand interaction for regulation of gene expression