An integrated ranking algorithm for efficient information computing in social networks

Social networks have ensured the expanding disproportion between the face of WWW stored traditionally in search engine repositories and the actual ever changing face of Web. Exponential growth of web users and the ease with which they can upload contents on web highlights the need of content controls on material published on the web. As definition of search is changing, socially-enhanced interactive search methodologies are the need of the hour. Ranking is pivotal for efficient web search as the search performance mainly depends upon the ranking results. In this paper new integrated ranking model based on fused rank of web object based on popularity factor earned over only valid interlinks from multiple social forums is proposed. This model identifies relationships between web objects in separate social networks based on the object inheritance graph. Experimental study indicates the effectiveness of proposed Fusion based ranking algorithm in terms of better search results.Comment: 14 pages, International Journal on Web Service Computing (IJWSC), Vol.3, No.1, March 201

The review of heterogeneous design frameworks/Platforms for digital systems embedded in FPGAs and SoCs

Systems-on-a-chip integrate specialized modules to provide well-defined functionality. In order to guarantee its efficiency, designersare careful to choose high-level electronic components. In particular,FPGAs (field-programmable gate array) have demonstrated theirability to meet the requirements of emerging technology. However,traditional design methods cannot keep up with the speed andefficiency imposed by the embedded systems industry, so severalframeworks have been developed to simplify the design process of anelectronic system, from its modeling to its physical implementation.This paper illustrates some of them and presents a comparative studybetween them. Indeed, we have selected design methods of SoC(ESP4ML and HLS4ML, OpenESP, LiteX, RubyRTL, PyMTL,SysPy, PyRTL, DSSoC) and NoC networks on OCN chip (PyOCN)and in general on FPGA (PRGA, OpenFPGA, AnyHLS, PYNQ, andPyLog).The objective of this article is to analyze each tool at several levelsand to discuss the benefit of each in the scientific community. Wewill analyze several aspects constituting the architecture and thestructure of the platforms to make a comparative study of thehardware and software design flows of digital systems.

Inner-suburban neighbourhoods, activist research and the social space of the commercial street

This paper tracks the transition of “creative city” planning from the gentrified downtown to the disinvested inner-suburbs. It attends particularly to contradictory notions of community mobilized by proponents of inner-suburban revitalization and by residents and business owners who daily inhabit inner-suburban commercial streets where cultural planning interventions are typically targeted. It further argues that those contradictory notions indicate immanent displacement pressure. The argument builds around data gleaned from an action research project in Toronto’s Mount Dennis neighbourhood, a former manufacturing neighbourhood that is now home to a large number of precariously employed new immigrants. We contend that community engaged research not only allows for an analysis of the race and class dimensions of creative city planning, it consolidates marginalized perspectives and opens up alternative possibilities for planning and development. We also claim that the relational, exploratory and sometimes fraught process of sharing knowledge with community-based researchers enriches critical research on the exclusionary politics of redevelopment planning

Cross-Layer Fragment Indexing based File Deduplication using Hyper Spectral Hash Duplicate Filter (HSHDF) for Optimized Cloud Storage

Cloud computing and storage processing is a big service for maintaining a large number of data in a centralized server to store and retrieve data depending on the use to pay as a service model. Due to increasing storage depending on duplicate copy presence during different sceneries, the increased size leads to increased cost. To resolve this problem, we propose a Cross-Layer Fragment Indexing (CLFI) based file deduplication using Hyper Spectral Hash Duplicate Filter (HSHDF) for optimized cloud storage. Initially, the file storage indexing easy carried out with Lexical Syntactic Parser (LSP) to split the files into blocks. Then comparativesector was created based on Chunk staking. Based on the file frequency weight, the relative Indexing was verified through Cross-Layer Fragment Indexing (CLFI). Then the fragmented index gets grouped by maximum relative threshold margin usingIntra Subset Near-Duplicate Clusters (ISNDC). The hashing is applied to get comparative index points based on hyper correlation comparer using Hyper Spectral Hash Duplicate Filter (HSHDF). This filter the near duplicate contentdepending on file content difference to identify the duplicates. This proposed system produces high performance compared to the other system. This optimizes cloudstorage and has a higher precision rate than other methods

Batch and Streaming Data Ingestion towards Creating Holistic Health Records

The healthcare sector has been moving toward Electronic Health Record (EHR) systems that produce enormous amounts of healthcare data due to the increased emphasis on getting the appropriate information to the right person, wherever they are, at any time. This highlights the need for a holistic approach to ingest, exploit, and manage these huge amounts of data for achieving better health management and promotion in general. This manuscript proposes such an approach, providing a mechanism allowing all health ecosystem entities to obtain actionable knowledge from heterogeneous data in a multimodal way. The mechanism includes diverse techniques for automatically ingesting healthcare-related information from heterogeneous sources that produce batch/streaming data, managing, fusing, and aggregating this data into new data structures (i.e., Holistic Health Records (HHRs)). The latter enable the aggregation of data coming from different sources, such as Internet of Medical Things (IoMT) devices, online/offline platforms, while to effectively construct the HHRs, the mechanism develops various data management techniques covering the overall data path, from data acquisition and cleaning to data integration, modelling, and interpretation. The mechanism has been evaluated upon different healthcare scenarios, ranging from hospital-retrieved data to patient platforms, combined with data obtained from IoMT devices, having produced useful insights towards its successful and wide adaptation in this domain. In order to implement a paradigm shift from heterogeneous and independent data sources, limited data exploitation, and health records, the mechanism has combined multidisciplinary technologies toward HHRs. Doi: 10.28991/ESJ-2023-07-02-03 Full Text: PD