Ivana Stamenković, Dušan Aleksić, Tatjana Đukić Živadinović · Balkan Social Science Review · 2023
Although the audience in the digital media space has more power than in the traditional media environment, as indicated by their ability to create, reshape and share content, media users’ behavior is shaped by the use of algorithms and big data management. Taking into consideration the fact that students use the internet and social media platforms daily, this paper aims to examine their perceptions and viewpoints on the operation of algorithms and data management on the Internet. According to a survey conducted by the authors, which consists of 200 respondents, two-thirds of students notice the results of the algorithmic personalization, filtered selection of content and news, and the customized display of content on social media. Even though 70% of them realize that user activities are continually monitored and that control over personal data online is taken over by large companies and/or a third party, most respondents express only moderate concern for their data online (82%), which further confirms the fact that only a small percentage of students (18%) almost always read the terms of use on a website, application, or internet service. Keywords: social media, big data, algorithms, students
Cited by 1Open access
Hua, Stephen Tran Dung. · DR-NTU (Nanyang Technological University) · 2012
The report presents the purpose, concept, technique, detail explanation, results and consideration of the project “Data Placement and Management Algorithms for Data Centers”. The project is part of a joint research of NTU School of Computer Engineering and School of Mathematics Science about “Self-Repairing Code”. The project developed a pioneer Website application which utilizes Projective Self-Repairing Code (PSRC) of the Self-Repairing Code family. It is to prove the correctness and applicableness of the PSRC for data distribution over the network. The code tries to deliver a new concept of an effective and efficient mechanism to recover data lost in a distributed system. Binary file is treated as data and according to this PSRC, the web application has achieved splitting file into parts, creating redundant parts, distributing these parts over the network storages, repairing any file part loss and reconstructing original file. The author has developed a dynamic interactive website with user-friendly features as a file repository system and implemented these abovementioned functionalities applying PSRC algorithm. The application is built using robust and adaptive VB.NET with rich library classes to manipulate binary file as well as utilize socket for file transmission over the network. The SQL database is used to assist in file’s information storage. Furthermore, techniques such as bitwise XOR and random selection of nodes are implemented to make the PSRC concepts possible. Error handling and software testing have been taken care of to make this a quality application. In conclusion, the project has built a quality online repository application which first ever realizes the PSRC.
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David Zhang, Xiaobo Li, Xiaogang Li · The Kluwer international series on Asian studies in computer and information science · 2001
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Yin Ya · 2013
With the development of critical theories and technologies in Internet of Things(IOT),as a key supporting technology,RFID has become one of the hotspots in the field of Internet of Things.Focusing on RFID data management,this paper describes and analyzes the research work on three aspects: algorithm,protocol and performance evaluation.In this paper,we introduce the research progress in RFID with anti-collision algorithm,authentication and privacy protection protocols,as well as performance evaluation of RFID systems in realistic settings.Finally,we outlook the future research directions and conclude.
Cited by 3
Sudhir Venkatesan, Puja Myles, Gerry P McCann et al. · 2015
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Zachary Predmore, Shira H. Fischer · Population Health Management · 2021
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Giorgia Carra, Jorge I. Salluh, Fernando José da Silva Ramos et al. · Journal of Critical Care · 2020
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Davide Mula · SHILAP Revista de lepidopterología · 2021
This paper intends to investigate the processing and exploitation of data (whether personal and not) through algorithms to understand the profiles of responsibility and the related mechanisms of accountability. In particular, the paper will try to understand how the security of automated and algorithmic decision-making processes can be verified ex post, due to their impact on privacy of both public and private entities.
Cited by 0Open access
Huizhi Li, X. D. Yu · Journal of Computational Methods in Sciences and Engineering · 2025
In the field of enterprise management accounting, the traditional manual input method is inefficient and error-prone in the face of the processing demand of massive invoice data. The intelligent management accounting tool proposed in this study, based on the improved K-Means algorithm, effectively improves the efficiency and accuracy of automatic invoice identification. The results show that the recognition accuracy of this tool is 98.63%, which is 5.83% higher than that of Canny algorithm (92.80%), and the average invoice processing speed is 5.34 invoices per second. This means that for a large enterprise that has to process thousands of invoices every day, intelligent management accounting tools can greatly increase the speed of data processing while ensuring high accuracy and can save a lot of labor costs every month. In addition, the tool can also repair the defects of invoice images in real time, adapt to the automatic identification of various types of invoices, and provide a new and efficient solution for enterprise financial data processing. The use of intelligent tools to enhance the ability of enterprises to analyze financial data has fundamentally changed the way financial data is processed.
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Xin Cao, Chunxiao Mei, Zhiyong Song et al. · Measurement Sensors · 2024
In order to solve the problem of difficulty in learning semantic pattern representations between user dynamic interest sequences using path based and knowledge graph based entity embedding methods, the author proposes research on spatiotemporal data modeling and prediction algorithms in intelligent management systems. The author first makes a preliminary analysis of the wireless network data (mainly the data of cellular mobile networks) obtained by Internet service providers, reveals that the data of adjacent base stations have temporal and spatial correlations, then establishes a hybrid deep learning model for spatio-temporal prediction, and proposes a new spatial model training algorithm. Finally, experiments were conducted using wireless network datasets to evaluate the performance of the model. The experimental results show that based on data analysis, it can be seen that the prediction of the system has effectively improved by 99%. The spatiotemporal data modeling and prediction algorithm proposed by the author in the intelligent management system significantly improves prediction accuracy.
Cited by 1Open access
Kishore Challa · 2025
Many analytical tools run off-line and sit in the back room. Someone assembles, formats, and makes sense of the results, who may or may not have anything to do with the decision-making processes. Who sees the results, when, and what they can do with it are pretty much pre-determined. This pre-specified result is then presented to the decision makers who may or may not do anything about it. It is then a one-way communication, feedback is usually not immediate, and it is hard to know what bits and pieces of information are of interest. Interactive tools, on the other hand, allow decision makers to dictate the conditions under which information will be released and in what form. They allow managers to examine different scenarios with relative ease and provide a great deal of scope for tailoring the inputs and the formats required. They enable feedback to be instantaneous and the decision maker is in complete control. In some sense, interactive tools are more like dashboards compared with static analytical models.
Cited by 0Open access
Microsoft Research · Bulletin of Miscellaneous Information (Royal Gardens Kew) · 2006
I will describe some algorithms for addressing some fundamental optimization problems that arise in the context of data storage and management. In the first part of the talk we will address the following question: How should we store data in order to effectively cope with non-uniform demand for data? How many copies of popular data objects do we need? Where should we store them for effective load balancing? In the second part of the talk we will address the issue of moving data objects quickly, to react to changing demand patterns. We will develop approximation algorithms for these problems. The first part of the talk is joint work with Golubchik, Khanna, Thurimella and Zhu. The second part is joint work with Kim and Wan. ©2006 Microsoft Corporation. All rights reserved.
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Pierangelo Veltri · Briefings in Bioinformatics · 2007
Mass spectrometry (MS) is a technique that is used for biological studies. It consists in associating a spectrum to a biological sample. A spectrum consists of couples of values (intensity, m/z), where intensity measures the abundance of biomolecules (as proteins) with a mass-to-charge ratio (m/z) present in the originating sample. In proteomics experiments, MS spectra are used to identify pattern expressions in clinical samples that may be responsible of diseases. Recently, to improve the identification of peptides/proteins related to patterns, MS/MS process is used, consisting in performing cascade of mass spectrometric analysis on selected peaks. Latter technique has been demonstrated to improve the identification and quantification of proteins/peptide in samples. Nevertheless, MS analysis deals with a huge amount of data, often affected by noises, thus requiring automatic data management systems. Tools have been developed and most of the time furnished with the instruments allowing: (i) spectra analysis and visualization, (ii) pattern recognition, (iii) protein databases querying, (iv) peptides/proteins quantification and identification. Currently most of the tools supporting such phases need to be optimized to improve the protein (and their functionalities) identification processes. In this article we survey on applications supporting spectrometrists and biologists in obtaining information from biological samples, analyzing available software for different phases. We consider different mass spectrometry techniques, and thus different requirements. We focus on tools for (i) data preprocessing, allowing to prepare results obtained from spectrometers to be analyzed; (ii) spectra analysis, representation and mining, aimed to identify common and/or hidden patterns in spectra sets or in classifying data; (iii) databases querying to identify peptides; and (iv) improving and boosting the identification and quantification of selected peaks. We trace some open problems and report on requirements that represent new challenges for bioinformatics.
Cited by 26Open access
Alfredo Cuzzocrea · SN Computer Science · 2026
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Singanallur Venkatakrishnan, K. Aditya Mohan, K. Beattie et al. · Electronic Imaging · 2016
Synchrotrons such as the Advanced Light Source (ALS) at Lawrence Berkeley National Laboratory are user facilities - they are sources of extremely bright X-ray beams, and scientists come from all over the world to perform experiments that require these beams. As the complexity of experiments has increased, and the size and rates of data sets has exploded, managing, analyzing and presenting the data collected at synchrotrons has been an increasing challenge. The ALS has partnered with high performance computing, fast networking, and applied mathematics groups to create a“super-facility”, giving users simultaneous access to the experimental, computational, and algorithmic resources to overcome this challenge. This combination forms an efficient closed loop, where data despite its high rate and volume is transferred and processed, in many cases immediately and automatically, on appropriate compute resources, and results are extracted, visualized, and presented to users or to the experimental control system, both to provide immediate insight and to guide decisions about subsequent experiments during beam-time. In this paper, We will present work done on advanced tomographic reconstruction algorithms to support users of the 3D micron-scale imaging instrument (Beamline 8.3.2, hard X-ray micro-tomography).
Cited by 9Open access
Aiichiro Nakano, Rajiv K. Kalia, Priya Vashishta · Computing in Science & Engineering · 1999
Highly efficient algorithms for massively parallel computers, interactive virtual environments for analyzing and steering simulations in real time, and data compression and mining schemes for input/output and knowledge discovery have led to rapid progress in large scale molecular dynamics simulations involving millions of atoms. Consequently, dynamic fracture of materials with realistic microstructures can now be modeled atom-by-atom.
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Francesco Capizzano · International Journal for Numerical Methods in Engineering · 2017
Summary The paper describes the main features of an automatic and three‐dimensional Cartesian mesher specifically designed for compressible inviscid/viscous flow solvers based on an immersed boundary technique. The development of a meshing tool able of conducting non‐isotropic cell refinements is a very tiresome task. The major difficulty is to imagine, at the pre‐design phase, a light but flexible data management, which minimizes the memory and CPUs' resources. In particular, the embedded geometry has to be detected by means of a fast and robust tagging procedure. Cells in proximity of the wall have to be refined in a proper way to adequately solve large flow gradients. Smooth variation of mesh density between differently refined zones has to be guaranteed to increase the flow solver robustness. A procedure to obtain accurate data on the geometry surfaces should be foresee. Here, a robust algorithm is developed to reconstruct a surface triangulation starting from the intersection points among volume cells and the geometry surfaces. The paper attempts to address all the above issues to help the readers in designing their own tools and suggesting them a way forward.
Cited by 36
Bogdan Danov, Daniela Gotseva · 2025
In the era of big data, effectively extracting value from huge and complex information flows is key. A set of techniques and paradigms necessary for the successful management and analysis of Big Data are examined. Data preprocessing is examined, and dimensionality reduction techniques, such as PCA and random projections, that optimize data for analysis are also discussed. We look at different storage and access models, as well as data processing paradigms, including batch processing and stream processing.
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D'AMORE, Fabrizio · IRIS Research product catalog (Sapienza University of Rome) · 1993
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Prakash M. Nadkarni · Genomics · 1995
A consensus framework map of a chromosome is the single most useful map of the chromosome, because of the amount of information it holds as well as the quality of the supporting data backing the putative order of its objects. We describe data structures and algorithms to assist in framework map maintenance and to answer queries about order and distance on genomic objects. We show how these algorithms are efficiently implemented in a client-server relational database. We believe that our data structures are particularly suitable for databases to support collaborative mapping efforts that use heterogeneous methodologies. We summarize two applications that use these algorithms: CHROMINFO, a database specifically designed for framework map maintenance; and the shared client-server database for the chromosome 12 genome center.
Cited by 5Open access