A Scalable Real Time Agent-Based Information Retrieval Engine

In distributed information retrieval systems, information in web should be ranked based on a combination of multiple features. Linear combination of ranks has been the dominant approach due to its simplicity and efficiency. Such a combination scheme in distributed infrastructure requires that ranks in resources or agents are comparable to each other. The main challenge is how to transform the raw rank values of different criteria appropriately to make them comparable before any combination. In this manuscript, we will demonstrate how to rank Web documents based on its resource-provided information stream and how to combine and incorporate several raking schemas in one time. The system was tested on the queries provided by a Text Retrieval Conference (TREC), and our experimental results showed that it is robust and efficient compared with similar platforms that used offline data resources.

Characterizing Topics in Social Media Using Dynamics of Conversation

Online social media provides massive open-ended platforms for users of a wide variety of backgrounds, interests, and beliefs to interact and debate, facilitating countless discussions across a myriad of subjects. With numerous unique voices being lent to the ever-growing information stream, it is essential to consider how the types of conversations that result from a social media post represent the post itself. We hypothesize that the biases and predispositions of users cause them to react to different topics in different ways not necessarily entirely intended by the sender. In this paper, we introduce a set of unique features that capture patterns of discourse, allowing us to empirically explore the relationship between a topic and the conversations it induces. Utilizing “microscopic” trends to describe “macroscopic” phenomena, we set a paradigm for analyzing information dissemination through the user reactions that arise from a topic, eliminating the need to analyze the involved text of the discussions. Using a Reddit dataset, we find that our features not only enable classifiers to accurately distinguish between content genre, but also can identify more subtle semantic differences in content under a single topic as well as isolating outliers whose subject matter is substantially different from the norm.

Inter-Level Feature Balanced Fusion Network for Street Scene Segmentation

Semantic segmentation, as a pixel-level recognition task, has been widely used in a variety of practical scenes. Most of the existing methods try to improve the performance of the network by fusing the information of high and low layers. This kind of simple concatenation or element-wise addition will lead to the problem of unbalanced fusion and low utilization of inter-level features. To solve this problem, we propose the Inter-Level Feature Balanced Fusion Network (IFBFNet) to guide the inter-level feature fusion towards a more balanced and effective direction. Our overall network architecture is based on the encoder–decoder architecture. In the encoder, we use a relatively deep convolution network to extract rich semantic information. In the decoder, skip-connections are added to connect and fuse low-level spatial features to restore a clearer boundary expression gradually. We add an inter-level feature balanced fusion module to each skip connection. Additionally, to better capture the boundary information, we added a shallower spatial information stream to supplement more spatial information details. Experiments have proved the effectiveness of our module. Our IFBFNet achieved a competitive performance on the Cityscapes dataset with only finely annotated data used for training and has been greatly improved on the baseline network.

Social Media as a Tool to Understand Behaviour on the Railways

Social media plays an increasing role in how passengers communicate to, and about, train operators. In response, train operators and other rail stakeholders are adopting social media to contact their users. There are a number of opportunities for tapping this big data information stream through the overt use of technology to analyse, filter and present social media, including filtering for operational staff, or sentiment mapping for strategy. However, this analysis is predicated on a number of assumptions regarding the manner in which social media is currently being used within a railway context. In the following chapter, we present data from studies of rail social media that shed light on how big data analysis of social media exchange can support the passenger. These studies highlight important factors such as the broad range of issues covered by social media (not just disruption), the idiosyncrasies of individual train operators that need to be taken into account within social media analysis, and the time critical nature of information during disruption.

Aspects of of protection human rights in inspection in cases of killings

The aim of the article is to present the protection of human rights in inspection in cases of killings. Analisys will be presented by aspects, which have been created by forensic tactics and forensic technique. Presentation of titular institution will covered the effects of carrying out the action on the dection process of the perpetrators of killings. The title factors in the protection of human rights in the conduct of investigations of killing cases include the essence of the inspection, rules for conducting the inspection, qualitative and quantitative selection of the inspection group, izolation of the inspection site, inspection stages, guide with a tracking dog, rules of inspection documentation, technical and process securing of the subject of inspection, post-inspection note, supplementary inspection, repeated inspection, continuation of the case. The factor of human rights protection in this article is understood as any activity of the organs of criminal proccedings related to the inspection of the scene of crime, aimed at respecting human rights. The measure of observance of human rights is the determination of a certain sequence of activities in the detection process, which is then followed during the implementation of this process, as well as the determination of the maximum quality of these activities, the intensity and content of the information stream stimulating the detection process as a whole, as well as individual segments or stages.

Design of Real Time Air Pollution Monitoring System Based on Web Application and Main-Memory Database

Air contamination issues are firmly connected to geographic areas. The current ecological observing frameworks have little spotlight on geographic data handling and continuous perception. Air quality checking framework. Sensor constituent on this scaffold depends on nano organized zinc oxide slender film blended utilizing soakedstufftrack. In this magazine, a spatial augmentation to fundamental reminiscencerecord is executed to help the capacity and record of virtual-world information. In the interim, noteworthy information is put away in disk-based spatial catalogue, giving the capacity of questioning and breaking down. A continuous air quality checking framework is structured and executed which can route and show information stream on constant.Natural checking is a methodical methodology for watching and contemplating the state of condition. For the sound person require taking in a spotless air yet because of expanding the transportation framework natural air get contaminated. Transport framework has the effect on condition where we live. Increment in vehicle offers ascend to expanding traffic related poison discharge. In this way, to follow the impact of this contamination on condition and soundness of individual it is important to follow the degree of contamination in urban and sub urban zones. Numerous wellbeing related issues are emerging from air contamination. In this manner, air quality observing is required so as to give valuable data about the contamination and can take proper measures to alleviate the negative effect at whatever point it is vital.

Information Radio Stations Business FM, Vesti FM and Kommersant FM: a Comparative Analysis of the Morning Air

The article presents the results of the second stage of the research titled “Transformation of the content strategies of modern radio and television broadcasting in the digital environment” carried out by a research team of the Department of Television and Radio Broadcasting, Faculty of Journalism, Moscow State University. The authors analyze the content of the morning broadcast of all-news radio stations of Moscow FM band (Business FM, Vesti FM, and Kommersant FM) in the period of 2018.05.14 to 2018.05.20 chosen by the continuous sampling method. The comprehensive study required working out a questionnaire of 25 questions to analyze various parameters from air time, running time, and type of program to interactive communication with audience. The study shows that all the three radio stations demonstrate a stable broadcast schedule and strip programming. Business FM and Kommersant FM broadcast linearly in a continuous information stream. Vesti FM includes long analytical talk-programs with experts and guests interacting with the audience via SMS. The content-analysis of the three radio stations’ morning broadcast enables the authors to confirm a previously advanced thesis that Business FM and Kommersant FM fall into the category of all-news radio stations, whereas Vesti FM does not. The latter, despite its wide variety of interprogram and structural elements, is transforming its format into news talk.

How doctors on social media can provide valid health information on novel coronavirus (Preprint)

UNSTRUCTURED In the wake of COVID-19, the information stream has overflowed with a mixture of valid knowledge, misinformation and constantly changing guidelines. The need for help in navigating what is trustworthy health information is great and the official channels are struggling to keep up. As a consequence we created a Facebook group where volunteer doctors would answer questions from laymen about the novel coronavirus. There is not much precedence in healthcare professional driven Facebook groups and the framework was thus invented on the go. We ended up with an approach without room for debate to keep the group calm, trustworthy and safe to enter for the inquirers. Substantial moderator effort was needed to ensure high quality and consistency through collaboration between the more than hundred doctors participating. In the end we were able to provide a much needed service to more than 34.000 people in Denmark in time of crisis.

Free Speech and Digital Discourse in Nicola Barker’s "H(A)PPY"

<p>Nicola Barker’s <em>H(A)PPY</em> (2017) depicts a dystopian future in which all speech is monitored and regulated. Politically dubious topics are flagged, metanarratives like religion and history are censored, and even words expressing heightened emotional states are marked as dangerous. Barker uses innovative techniques to visualise the warping of language under conditions of totalitarian surveillance. In analysing Barker’s novel, this paper applies the findings of digital discourse studies to the novel’s content while arguing that its experimental techniques reflect a distinct break from the digital information stream. Barker’s innovations are a formal route to escape the deadlock of our current politics.</p>