Academic literature on the topic 'Internet searching – Statistical methods'
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Journal articles on the topic "Internet searching – Statistical methods"
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Ibrahim, Hamza Awad Hamza, Omer Radhi A. L. Zuobi, Awad M. Abaker, and Musab B. Alzghoul. "A Hybrid Online Classifier System for Internet Traffic Based on Statistical Machine Learning Approach and Flow Port Number." Applied Sciences 11, no. 24 (December 20, 2021): 12113. http://dx.doi.org/10.3390/app112412113.
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Internet traffic classification is a beneficial technique in the direction of intrusion detection and network monitoring. After several years of searching, there are still many open problems in Internet traffic classification. The hybrid classifier combines more than one classification method to identify Internet traffic. Using only one method to classify Internet traffic poses many risks. In addition, an online classifier is very important in order to manage threats on traffic such as denial of service, flooding attack and other similar threats. Therefore, this paper provides some information to differentiate between real and live internet traffic. In addition, this paper proposes a hybrid online classifier (HOC) system. HOC is based on two common classification methods, port-base and ML-base. HOC is able to perform an online classification since it can identify live Internet traffic at the same time as it is generated. HOC was used to classify three common Internet application classes, namely web, WhatsApp and Twitter. HOC produces more than 90% accuracy, which is higher than any individual classifiers.
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Potkány, Marek, and Alexandra Hajduková. "Social Networks and their Importance in Job Searching of College Students." Verslas: Teorija ir Praktika 16, no. 1 (March 30, 2015): 75–83. http://dx.doi.org/10.3846/btp.2015.462.
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At present, in every sphere of human activity, using modern ICT is considered as a matter of course. Several human resources management institutions are aware of the potential of social networks in estabilishing and building relationships with their target groups. It is a trend to create job portals in social networks. These are currently an integrated part of communication with target audience and therefore also an objects of attention and reflexions. It is also the topic of this paper. The goal of this research is to determine the level of use of social networks by college students in Slovakia. Part of the research is also to discover the effect of social networks on job searching of a selected sample of students. The research was conducted on a sample of 407 slovak students. A questioning method in form of an online questionnaire was used. The obtained results were processed using methods of descriptive and test statistics. We studied the significance of gender on the frequency of using the internet to search for job opportunities via social networks, as well as the ability to apprehend the importance of personal presentation on social networks. The statistical testing did not prove any significant difference between men and women in the question of frequency of using internet to search for job opportunities, nor in the ability to apprehend the importance of personal presentation on social networks. A statistically significant difference in gender was proven only in case of using social networks in job searching. Women tend to use social networks to find jobs more often than men. These statements are proved by the results of tests of significance of mean changes at the 5% significance level, which means that they are valid with 95% probability.
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Elovici, Yuval, Chanan Glezer, and Bracha Shapira. "Enhancing customer privacy while searching for products and services on the world wide web." Internet Research 15, no. 4 (September 1, 2005): 378–99. http://dx.doi.org/10.1108/10662240510615164.
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PurposeTo propose a model of a privacy‐enhanced catalogue search system (PECSS) in an attempt to address privacy threats to consumers, who search for products and services on the world wide web.Design/methodology/approachThe model extends an agent‐based architecture for electronic catalogue mediation by supplementing it with a privacy enhancement mechanism. This mechanism introduces fake queries into the original stream of user queries, in an attempt to reduce the similarity between the actual interests of users (“internal user profile”) and the interests as observed by potential eavesdroppers on the web (“external user profile”). A prototype was constructed to demonstrate the feasibility and effectiveness of the model.FindingsThe evaluation of the model indicates that, by generating five fake queries per each original user query, the user's profile is hidden most effectively from any potential eavesdropper. Future research is needed to identify the optimal glossary of fake queries for various clients. The model also should be tested against various attacks perpetrated against the mixed stream of original and fake queries (i.e. statistical clustering).Research limitations/implicationsThe model's feasibility was evaluated through a prototype. It was not empirically tested against various statistical methods used by intruders to reveal the original queries.Practical implicationsA useful architecture for electronic commerce providers, internet service providers (ISP) and individual clients who are concerned with their privacy and wish to minimize their dependencies on third‐party security providers.Originality/valueThe contribution of the PECSS model stems from the fact that, as the internet gradually transforms into a non‐free service, anonymous browsing cannot be employed any more to protect consumers' privacy, and therefore other approaches should be explored. Moreover, unlike other approaches, our model does not rely on the honesty of any third mediators and proxies that are also exposed to the interests of the client. In addition, the proposed model is scalable as it is installed on the user's computer.
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Kerneža, Maja, and Metka Kordigel Aberšek. "ONLINE READING IN DIGITAL LEARNING ENVIRONMENTS FOR PRIMARY SCHOOL STUDENTS." Problems of Education in the 21st Century 80, no. 6 (December 25, 2022): 836–50. http://dx.doi.org/10.33225/pec/22.80.836.
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Learning environments and teaching methods have been constantly changing over the past decades. As the shift in the learning environment is primarily toward a physical to an online learning environment, this study examines how to enable younger students to select appropriate content for learning in digital learning environments that they can then successfully read and evaluate using appropriate strategies. The study is based on 54 in-depth case studies. Using the Internet reciprocal teaching method (IRT), 54 implementers trained 54 primary school students from first to fifth grade in basic computer skills, Internet information searching, and website navigation, as well as analysing data obtained using the TICA Phase 1, 2, and 3 Checklists, the implementers' report, and the children notes in a text editor. Triangulation of the data in combination with selected statistical methods shows that there are differences in the use of the method between students according to age. While the latter can use an unadopted form of the method, younger students need some adjustments, which are suggested in the light of previous research. Keywords: digital literacy, e-reading, primary school, internet reciprocal teaching, online learning
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GAUTAMA, H., and A. J. C. VAN GEMUND. "SYMBOLIC PERFORMANCE ESTIMATION OF SPECULATIVE PARALLEL PROGRAMS." Parallel Processing Letters 13, no. 04 (December 2003): 513–24. http://dx.doi.org/10.1142/s0129626403001471.
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Speculative parallelism refers to searching in parallel for a solution, such as finding a pattern in a data base, where finding the first solution terminates the whole parallel process. Different performance prediction methods are required as compared to traditional parallelism. In this paper we introduce an analytical approach to predict the execution time distribution of data-dependent parallel programs that feature N-ary and binary speculative parallel compositions. The method is based on the use of statistical moments which allows program execution time distribution to be approximated at O(1) solution complexity. Measurement results for synthetic distributions indicate an accuracy that lies in the percent range while for empirical distributions on internet search engines the prediction accuracy is acceptable, provided sufficient workload unimodality.
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Yin, Rong, and David M. Neyens. "Online Health Resource Use by Individuals With Inflammatory Bowel Disease: Analysis Using the National Health Interview Survey." Journal of Medical Internet Research 22, no. 9 (September 24, 2020): e15352. http://dx.doi.org/10.2196/15352.
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Background The internet has enabled convenient and efficient health information searching which is valuable for individuals with chronic conditions requiring some level of self-management. However, there is little research evaluating what factors may impact the use of the internet for health-related tasks for specific clinical populations, such as individuals with inflammatory bowel diseases. Objective Our goal was to investigate the factors that influence internet use in acquiring health information by individuals with inflammatory bowel diseases. Specifically, we identified factors associated with internet searching behavior and using the internet for completing health-related tasks. Methods We used 2016 National Health Interview Survey weighted data to develop logistic regression models to predict the likelihood that individuals with inflammatory bowel diseases would use the internet for 2 types of tasks: seeking health information through online searches and using the internet to perform health-related tasks including scheduling appointments and emailing care providers. Results 2016 National Health Interview Survey weighted data include more than 3 million weighted adult respondents with inflammatory bowel diseases (approximately 1.29% of adults in the weighted data set). Our results suggest that approximately 66.3% of those with inflammatory bowel diseases reported using the internet at least once a day, and approximately 14.7% reported being dissatisfied with their current health care. About 62.3% of those with inflammatory bowel diseases reported that they had looked up health information online, 16.3% of those with inflammatory bowel diseases reported that they had scheduled an appointment with a health care provider online, and 21.6% reported having used a computer to communicate with a health provider by email. We found that women who were self-regulating their care were more likely to look up health information online than others. Both middle-aged and older adults with inflammatory bowel diseases who were unsatisfied with their current health care were less likely to look up health information online. Frequent internet users who were worried about medical costs were more likely to look up health information online. Similarly, the results from our statistical models suggest that individuals with inflammatory bowel diseases who were frequent internet users were more likely to use the internet for specific health-related tasks. Additionally, women with inflammatory bowel diseases who reported being married were less likely to use the internet for specific health-related tasks. Conclusions For those with inflammatory bowel diseases, there are additional socioeconomic and behavioral factors that impact the use of the internet for health information and health-related tasks. Future research should evaluate how these factors moderate the use of the internet and identify how online resources can support clinical populations in ways that improve access to information, support health self-management, and subsequently improve health outcomes.
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Fedorchenko, Elena, Evgenia Novikova, Igor Kotenko, Diana Gaifulina, Olga Tushkanova, Dmitry Levshun, Alexey Meleshko, Ivan Murenin, and Maxim Kolomeec. "THE SECURITY AND PRIVACY MEASURING SYSTEM FOR THE INTERNET OF THINGS DEVICES." Voprosy kiberbezopasnosti, no. 5(51) (2022): 28–46. http://dx.doi.org/10.21681/2311-3456-2022-5-28-46.
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The purpose of the article: elimination of the gap in existing need in the set of clear and objective security and privacy metrics for the IoT devices users and manufacturers and an absence of such a set incorporating the interconnected security and privacy metrics, the algorithms for their calculation and generation of the integral clear and objective score by the development of the security and privacy measuring system for the IoT devices. Research method: theoretical and system analysis for determination and classification of the security and privacy metrics, semantic analysis for generating of the semantic model of personal data processing scenarios, analytical modeling methods for generating of the attack traces, log analysis methods, statistical methods and machine learning methods for searching of the anomalies in device behavior, development of the database and software implementing the proposed security and privacy measuring system. The result obtained: the security and privacy measuring system for the IoT devices users and manufacturers is proposed. The proposed system allows automated calculation of the security and privacy metrics based on the available data on the device and generation of the integral security and privacy score. The hierarchy of security and privacy metrics is developed in the scope of the proposed system. The proposed metrics are calculated using static and dynamic data on the device and its behavior. Original algorithms for calculation of the outlined metrics are developed, including the algorithms for calculation of the integral security and privacy score. The architecture of the security measuring system is developed. It integrates the components implementing the developed algorithms for metrics calculation. The system operation is demonstrated on the case study. The area of use of the proposed approach - the developed security and privacy measuring system can be used by the IoT devices manufacturers to analyse their security and privacy, and to provide the users with simple and clear security and privacy metrics. Novelty: the hierarchy of static and dynamic security and privacy metrics for the Internet of Things is developed; the approach to security and privacy assessment for the Internet of Things on the basis of the developed metrics and available data is proposed; novel algorithms for metrics calculation are developed; novel algorithms for integral metrics calculation considering available data are developed. Contribution: Fedorchenko E. – development of the approach, metrics hierarchy, and system architecture, problem statement for the components and their development, Novikova E. – the component for calculation of privacy risks, the component for calculation of integral risk scores, Kotenko I. – project management, problem statement, system architecture, Gaifulina D. – the component for event logs processing and integration, Tushkanova O., Murenin I. – the component for calculation of the dynamic risks score using statistical methods and machine learning, Levshun D. – metrics database, the component for calculation of the static risk score, Meleshko A. – the component for readability assessment, Kolomeets M. – the component for privacy risks assessment on the basis of *.apk files, the component for the dynamic risk score calculation considering attacks traces. All authors participated in the writing of the article.
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Salbach, Nancy M., Susan B. Jaglal, Nicol Korner-Bitensky, Susan Rappolt, and Dave Davis. "Practitioner and Organizational Barriers to Evidence-based Practice of Physical Therapists for People With Stroke." Physical Therapy 87, no. 10 (October 1, 2007): 1284–303. http://dx.doi.org/10.2522/ptj.20070040.
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Background and Purpose The purpose of this study was to identify practitioner barriers (education, attitudes and beliefs, interest and perceived role, and self-efficacy) and organizational barriers (perceived support and resources) to physical therapists’ implementation of evidence-based practice (EBP) for people with stroke. Subjects The participants were 270 physical therapists providing services to people with stroke in Ontario, Canada. Methods A cross-sectional mail survey was conducted. Results Only half of respondents had learned the foundations of EBP in their academic preparation or received training in searching or appraising research literature. Although 78% agreed that research findings are useful, 55% agreed that a divide exists between research and practice. Almost all respondents were interested in learning EBP skills; however, 50% indicated that physical therapists should not be responsible for conducting literature reviews. Average self-efficacy ratings were between 50% and 80% for searching and appraising the literature and below 50% for critically appraising psychometric properties and understanding statistical analyses. Despite Internet access at work for 80% of respondents, only 8% were given protected work time to search and appraise the literature. Discussion and Conclusion Lack of education, negative perceptions about research and physical therapists’ role in EBP, and low self-efficacy to perform EBP activities represent barriers to implementing EBP for people with stroke that can be addressed through continuing education. Organizational provision of access to Web-based resources is likely insufficient to enhance research use by clinicians.
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MIŠČENKO, Olga. "The Importance of a Teacher in a Distance Education and the Progressive Methods of Teaching in a Virtual Learning Environment." Coactivity: Philology, Educology 22, no. 2 (December 19, 2014): 97–104. http://dx.doi.org/10.3846/cpe.2014.241.
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The purpose of the article is to analyze the experience of the first work years of teaching the students, who study by distance, to compare other authors’ experience and to examine the advantages of Moodle virtual learning environment (VLE), searching for new applications of it. The relevance of e-learning is noted. It is affirmed that metacognitive learning strategies are typical for learning foreign languages in virtual environment. It is said that the Internet is a tool that ensures studies by distance. It is said that raising the qualification and learning by distance allows a responsible employee to improve foreign language skills while lifelong learning. VLE adaptability for teaching and studying English is being discussed. It is stated that the Internet conditions all types of methods in the virtual environment, application, and its existence expands and deepens the learning approach. In the paper it is claimed that the Moodle VLE function is to improve the learning process to ensure a high level of expertise and the objectivity of assessment. Studying in conventional way and in the virtual environment are briefly compared. Moodle virtual learning environment application objectives to learning outcomes, emphasizing the importance of the traditional teaching methods, the student’s responsibility to call attention to the learning process and system characteristics are defined. It is noted that learning in the virtual environment is based on the principles of epistemology, therefore the Moodle system meets the didactic tasks. The virtual learning environment possibilities ensure a very good feedback and increase students’ motivation, and, consequently, that provides better knowledge. It is emphasized that while teaching by distance, the teacher’s responsibility, his role in the development of educational material and the course tasks have increased. Some specific cases for various forms of studies and exercises to perform in the Moodle e-system are given. Some statistical data demonstrate the improvement of the quality of knowledge due to the Moodle system application for training foreign language.
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Malykh, O. E., and A. F. Khurmatullina. "ASSESSMENT OF LABOR RESOURCES AND EMPLOYMENT STRUCTURE IN THE MILLION-PLUS CITIES OF RUSSIA." Social & labor researches 46, no. 1 (2022): 55–63. http://dx.doi.org/10.34022/2658-3712-2022-46-1-55-63.
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The object of the study is municipalities with a population of more than 1 million people (million-plus cities). The aim of the article is to prepare a methodology for assessing labor resources and the employment structure in the context of large cities of the Russian Federation. The authors use the following methods: statistical analysis, aggregation and normalization of private indicators, analysis of scientific literature, analysis of materials provided by the regions of the Russian Federation, and Internet sources. The result of the study is the assessment of the state and identification of factors affecting labor resources and the employment structure in Russian million-plus cities, as well as the preparation of methodological recommendations for public authorities of the Russian regions on the regulation of labor resources and the employment structure in large cities of the Russian Federation. The scope of application of the research results — the materials of the scientific study may be used by federal and regional executive authorities that carry out the functions of developing and implementing the state employment policy, when searching for reserves to improve the organizational mechanism of indirect impact on the labor market of large cities, as well as preparing proposals to increase the stability of labor markets in Russia’s million-plus cities to external influences.
Dissertations / Theses on the topic "Internet searching – Statistical methods"
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Wright, Christopher M. "Using Statistical Methods to Determine Geolocation Via Twitter." TopSCHOLAR®, 2014. http://digitalcommons.wku.edu/theses/1372.
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With the ever expanding usage of social media websites such as Twitter, it is possible to use statistical inquires to form a geographic location of a person using solely the content of their tweets. According to a study done in 2010, Zhiyuan Cheng, was able to detect a location of a Twitter user within 100 miles of their actual location 51% of the time. While this may seem like an already significant find, this study was done while Twitter was still finding its ground to stand on. In 2010, Twitter had 75 million unique users registered, as of March 2013, Twitter has around 500 million unique users. In this thesis, my own dataset was collected and using Excel macros, a comparison of my results to that of Cheng’s will see if the results have changed over the three years since his study. If found to be that Cheng’s 51% can be shown more efficiently using a simpler methodology, this could have a significant impact on Homeland Security and cyber security measures.
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Deetjen, Ulrike. "Internet use and health : a mixed methods analysis using spatial microsimulation and interviews." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:92b1d35c-1aed-435d-8daa-18b1cd9ccaa1.
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Internet use is considered a lever for empowering patients, levelling inequalities and reducing healthcare expenditure. However, with digital inclusion, health provision quality and health system efficiency high on the UK and EU policy agendas, we need to better understand the relationship between Internet use and health outcomes to assess potential benefits and adverse effects. This research addresses the question of how Internet use influences individuals' health service use and their perceived health in the context of England. Focusing on health information-seeking, it analyses variations across different kinds of users, mechanisms between Internet use and both health outcomes, and the role of individual and contextual factors in this relationship. To answer this question, this research uses a mixed methods approach. Quantitative data from the Oxford Internet Surveys (OxIS), the English census and Hospital Episode Statistics (HES) was connected through spatial microsimulation based on output areas. Qualitative data was collected through semi-structured, face-to-face interviews, primarily with former OxIS participants from output areas in the quantitative strand. The quantitative data was revisited based on emerging interview themes. The results indicate that Internet use influences perceived health and health service use via various mechanisms based on the Internet's content, mediation and connection affordances. However, the boundaries between users and non-users are blurry and outcomes vary for different types of individuals, classified here as learners, pragmatists, sceptics, worriers, delegators and adigitals. Age, education, socioeconomic status, long-term health conditions, and geographic context influence Internet use and health outcomes separately, while the social context shapes their relationship too. These findings advance the theoretical understanding of Internet-based health outcomes, and provide practical implications for health professionals and policymakers with insights down to the local level. Moreover, this research demonstrates how novel insights for public wellbeing can be derived from qualitatively enriched secondary data in privacy-preserving and cost-effective ways.
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Mursia, Placido. "Multi-antenna methods for scalable beyond-5G access networks." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS532.
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L’augmentation exponentielle des équipements d’utilisateurs sans fil (UEs) et des services des réseaux associés aux déploiements actuels de cinquième génération (5G) pose plusieurs défis de conception sans précédent qui doivent être résolus avec l’avènement des futurs réseaux au-delà de la 5G. Plus précisément, la demande croissante de débits de données élevés ainsi que la nécessité de desservir un grand nombre d’appareils hétérogènes, allant des téléphones mobiles classiques aux objets connectés formant l’internet des objets (IoT), motivent l’étude de nouveaux schémas de traitement et de transmission du signal. À cet égard, les sorties multiples massives à entrées multiples (massive MIMO) sont une technologie d’accès bien établie, qui permet de desservir plusieurs dizaines d’UEs en utilisant lesmêmes ressources temps-fréquence au moyen de techniques de formation de faisceau hautement directionnelles. Cependant, le massive MIMO présente des problèmes d’évolutivité dans les scénarios accès massif où la population UE est composée d’un grand nombre de périphériques hétérogènes. En effet, si la disponibilité d’un grand nombre d’antennes dans les émetteurs-récepteurs massive MIMO apporte des gains de performances substantiels, elle augmente également considérablement la surcharge et la complexité du système. Plus précisément, la dimensionnalité élevée des canaux nécessite l’allocation de ressources temps-fréquence considérables pour acquérir les informations d’état de canal (CSI) et se traduit par de grandes opérations matricielles pour construire des précodeurs/décodeurs. De plus, dans le contexte de communications de multidiffusion comme, par exemple, la mise en cache périphérique sans fil ou la diffusion de messages critiques pour la mission, les techniques d’antennes multiples conventionnelles présentent des taux de disparition lorsque le nombre d’UEs augmente même dans le régime d’antenne massif. Enfin, le grand nombre de chaînes de radiofréquences (RF) associées aux émetteurs-récepteurs massive MIMO, qui sont utilisés pour contrer les pertes de propagation dans des environnements difficiles tels que, par exemple, à des fréquences d’ondes millimétriques (mmWave), se heurte au budget de puissance limité des appareils IoT. Dans cette thèse, nous proposons de nouvelles méthodes à antennes multiples évolutives pour l’amélioration des performances dans les scénarios d’intérêt susmentionnés. Plus précisément, nous décrivons le rôle fondamental joué par le CSI statistique qui peut être mis à profit pour réduire à la fois la complexité et la surcharge pour l’acquisition de CSI et pour la suppression des interférences multi-utilisateurs. En effet, lorsque les UEs sont équipés au moins de duex antennes, leurs propriétés de sélectivité spatiale peuvent être exploitées pour imposer une orthogonalité statistique parmi les transmissions interférentes. De plus, nous exploitons les communications de périphérique à périphérique (D2D) pour surmonter le goulot d’étranglement fondamental de la multidiffusion conventionnelle. En particulier, nous exploitons les capacités de précodage d’un émetteur multi-antennes pour sélectionner soigneusement les UEs dans des conditions de canal favorables, qui à leur tour agissent comme des relais opportunistes et retransmettent le message via les liaisons D2D. Enfin, dans le cadre des communications mmWave, nous explorons les avantages des surfaces intelligentes reconfigurables (RISs) récemment proposées, qui sont un catalyseur clé de l’innovation grâce à leur structure intrinsèquement passive qui permet de contrôler l’environnement de propagation et de contrer efficacement les pertes de propagation. En particulier, nous utilisons la formation de faisceaux passive au niveau du RIS, c’est-à-dire sans aucune dépense d’énergie significative, ainsi que la formation de faisceaux active conventionnelle au niveau de l’émetteur pour augmenter considérablement les performances du réseauThe exponential increase of wireless user equipments (UEs) and network services associated with current 5G deployments poses several unprecedented design challenges that need to be addressed with the advent of future beyond-5G networks and novel signal processing and transmission schemes. In this regard, massive MIMO is a well-established access technology, which allows to serve many tens of UEs using the same time-frequency resources. However, massive MIMO exhibits scalability issues in massive access scenarios where the UE population is composed of a large number of heterogeneous devices. In this thesis, we propose novel scalable multiple antenna methods for performance enhancement in several scenarios of interest. Specifically, we describe the fundamental role played by statistical channel state information (CSI) that can be leveraged for reduction of both complexity and overhead for CSI acquisition, and for multiuser interference suppression. Moreover, we exploit device-to-device communications to overcome the fundamental bottleneck of conventional multicasting. Lastly, in the context of millimiter wave communications, we explore the benefits of the recently proposed reconfigurable intelligent surfaces (RISs). Thanks to their inherently passive structure, RISs allow to control the propagation environment and effectively counteract propagation losses and substantially increase the network performance
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Abdel-Jaber, Hussein F. "Performance Modelling and Evaluation of Active Queue Management Techniques in Communication Networks. The development and performance evaluation of some new active queue management methods for internet congestion control based on fuzzy logic and random early detection using discrete-time queueing analysis and simulation." Thesis, University of Bradford, 2009. http://hdl.handle.net/10454/4261.
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Since the field of computer networks has rapidly grown in the last two decades, congestion control of traffic loads within networks has become a high priority. Congestion occurs in network routers when the number of incoming packets exceeds the available network resources, such as buffer space and bandwidth allocation. This may result in a poor network performance with reference to average packet queueing delay, packet loss rate and throughput. To enhance the performance when the network becomes congested, several different active queue management (AQM) methods have been proposed and some of these are discussed in this thesis. Specifically, these AQM methods are surveyed in detail and their strengths and limitations are highlighted. A comparison is conducted between five known AQM methods, Random Early Detection (RED), Gentle Random Early Detection (GRED), Adaptive Random Early Detection (ARED), Dynamic Random Early Drop (DRED) and BLUE, based on several performance measures, including mean queue length, throughput, average queueing delay, overflow packet loss probability, packet dropping probability and the total of overflow loss and dropping probabilities for packets, with the aim of identifying which AQM method gives the most satisfactory results of the performance measures. This thesis presents a new AQM approach based on the RED algorithm that determines and controls the congested router buffers in an early stage. This approach is called Dynamic RED (REDD), which stabilises the average queue length between minimum and maximum threshold positions at a certain level called the target level to prevent building up the queues in the router buffers. A comparison is made between the proposed REDD, RED and ARED approaches regarding the above performance measures. Moreover, three methods based on RED and fuzzy logic are proposed to control the congested router buffers incipiently. These methods are named REDD1, REDD2, and REDD3 and their performances are also compared with RED using the above performance measures to identify which method achieves the most satisfactory results. Furthermore, a set of discrete-time queue analytical models are developed based on the following approaches: RED, GRED, DRED and BLUE, to detect the congestion at router buffers in an early stage. The proposed analytical models use the instantaneous queue length as a congestion measure to capture short term changes in the input and prevent packet loss due to overflow. The proposed analytical models are experimentally compared with their corresponding AQM simulations with reference to the above performance measures to identify which approach gives the most satisfactory results. The simulations for RED, GRED, ARED, DRED, BLUE, REDD, REDD1, REDD2 and REDD3 are run ten times, each time with a change of seed and the results of each run are used to obtain mean values, variance, standard deviation and 95% confidence intervals. The performance measures are calculated based on data collected only after the system has reached a steady state. After extensive experimentation, the results show that the proposed REDD, REDD1, REDD2 and REDD3 algorithms and some of the proposed analytical models such as DRED-Alpha, RED and GRED models offer somewhat better results of mean queue length and average queueing delay than these achieved by RED and its variants when the values of packet arrival probability are greater than the value of packet departure probability, i.e. in a congestion situation. This suggests that when traffic is largely of a non bursty nature, instantaneous queue length might be a better congestion measure to use rather than the average queue length as in the more traditional models.
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"Searching for the contemporary and temporal causal relations from data." 2012. http://library.cuhk.edu.hk/record=b5549605.
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因果分析由于可以刻画随机事件之间的关系而被关注，而图模型则是描述因果关系的重要工具。在图模型框架中，数据集中隐含的因果关系被表示为定义在这个数据集上的贝叶斯网络，通过贝叶斯网络学习就可以完成数据集上的因果关系挖掘。因此,贝叶斯网络学习在因果分析中具有非常重要的作用。在本文中，我们提出了一种二段式的贝叶斯网络学习算法。在第一阶段，此算法从数据中构建出马尔可夫随机场。在第二阶段，此算法根据学习到的条件随机场构造出贝叶斯网络。本文中提出的二段式贝叶斯网络学习算法具有比现有算法更高的准确率，而且这种二段式算法中的一些技术可以很容易的被应用于其他贝叶斯网络学习算法当中。此外，通过与其他的时间序列中的因果分析模型（例如向量自回归和结构向量自回归模型）做比较，我们可以看出二段式的贝叶斯网络学习算法可以被用于时间序列的因果分析。 通过在真实数据集上的实验，我们证明的二段式贝叶斯网络学习算法在实际问题中的可用性。本文开始介绍了基于约束的贝叶斯网络学习框架，其中的代表作是SGS 算法。在基于约束的贝叶斯网络学习框架中，如何减小测试条件独立的搜索空间是提高算法性能的关键步骤。二段式贝叶斯网络学习算法的核心即是研究如何减小条件独立测试的搜索空间。为此，我们证明了通过马尔可夫随机场来确定贝叶斯网络的结构可以有效的减小条件独立测试的计算复杂性以及增加算法的稳定性。在本文中，偏相关系数被用来度量条件独立。这种方法可用于基于约束的贝叶斯网络学习算法。具体来说，本文证明了在给定数据集的生成模型为线性的条件下，偏相关系数可被用于度量条件独立。而且本文还证明了高斯模型是线性结构方程模型的一个特例。本文比较了二段式的贝叶斯网络学习算法与当前性能最佳的贝叶斯算法在一系列真实贝叶斯网络上的表现。
文章的最后一部分研究了二段式的贝叶斯网络学习算法在时间序列因果分析中的应用。在这部分工作中，我们首先证明了结构向量自回归模型模型在高斯过程中不能发现同时期的因果关系。失败的原因是结构向量自回归模型不能满足贝叶斯网络的忠实性条件。因此，本文的最后一部分提出了一种区别于现有工作的基于贝叶斯网络的向量自回归和结构向量自回归模型学习算法。并且通过实验证明的算法在实际问题中的可用性。
Causal analysis has drawn a lot of attention because it provides with deep insight of relations between random events. Graphical model is a dominant tool to represent causal relations. Under graphical model framework, causal relations implied in a data set are captured by a Bayesian network defined on this data set and causal discovery is achieved by constructing a Bayesian network from the data set. Therefore, Bayesian network learning plays an important role in causal relation discovery. In this thesis, we develop a Two-Phase Bayesian network learning algorithm that learns Bayesian network from data. Phase one of the algorithm learns Markov random fields from data, and phase two constructs Bayesian networks based on Markov random fields obtained. We show that the Two-Phase algorithm provides state-of-the-art accuracy, and the techniques proposed in this work can be easily adopted by other Bayesian network learning algorithms. Furthermore, we present that Two-Phase algorithm can be used for time series analysis by evaluating it against a series of time series causal learning algorithms, including VAR and SVAR. Its practical applicability is also demonstrated through empirical evaluation on real world data set.
We start by presenting a constraint-based Bayesian network learning framework that is a generalization of SGS algorithm [86]. We show that the key step in making Bayesian networks to learn efficiently is restricting the search space of conditioning sets. This leads to the core of this thesis: Two-Phase Bayesian network learning algorithm. Here we show that by learning Bayesian networks fromMarkov random fields, we efficiently reduce the computational complexity and enhance the reliability of the algorithm. Besides the proposal of this Bayesian network learning algorithm, we use zero partial correlation as an indicator of conditional independence. We show that partial correlation can be applied to arbitrary distributions given that data are generated by linear models. In addition, we prove that Gaussian distribution is a special case of linear structure equation model. We then compare our Two-Phase algorithm to other state-of-the-art Bayesian network algorithms on several real world Bayesian networks that are used as benchmark by many related works.
Having built an efficient and accurate Bayesian network learning algorithm, we then apply the algorithm for causal relation discovering on time series. First we show that SVAR model is incapable of identifying contemporaneous causal orders for Gaussian process because it fails to discover the structures faithful to the underlying distributions. We also develop a framework to learn true SVAR and VAR using Bayesian network, which is distinct from existing works. Finally, we show its applicability to a real world problem.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Wang, Zhenxing.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2012.
Includes bibliographical references (leaves 184-195).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstract also in Chinese.
Abstract --- p.i
Acknowledgement --- p.v
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Causal Relation and Directed Graphical Model --- p.1
Chapter 1.2 --- A Brief History of Bayesian Network Learning --- p.3
Chapter 1.3 --- Some Important Issues for Causal BayesianNetwork Learning --- p.5
Chapter 1.3.1 --- Learning Bayesian network locally --- p.6
Chapter 1.3.2 --- Conditional independence test --- p.7
Chapter 1.3.3 --- Causation discovery for time series --- p.8
Chapter 1.4 --- Road Map of the Thesis --- p.10
Chapter 1.5 --- Summary of the Remaining Chapters --- p.12
Chapter 2 --- Background Study --- p.14
Chapter 2.1 --- Notations --- p.14
Chapter 2.2 --- Formal Preliminaries --- p.15
Chapter 2.3 --- Constraint-Based Bayesian Network Learning --- p.24
Chapter 3 --- Two-Phase Bayesian Network Learning --- p.33
Chapter 3.1 --- Two-Phase Bayesian Network Learning Algorithm --- p.35
Chapter 3.1.1 --- Basic Two-Phase algorithm --- p.37
Chapter 3.1.2 --- Two-Phase algorithm with Markov blanket information --- p.59
Chapter 3.2 --- Correctness Proof and Complexity Analysis --- p.73
Chapter 3.2.1 --- Correctness proof --- p.73
Chapter 3.2.2 --- Complexity analysis --- p.81
Chapter 3.3 --- Related Works --- p.83
Chapter 3.3.1 --- Search-and-score algorithms --- p.84
Chapter 3.3.2 --- Constraint-based algorithms --- p.85
Chapter 3.3.3 --- Other algorithms --- p.86
Chapter 4 --- Measuring Conditional Independence --- p.88
Chapter 4.1 --- Formal Definition of Conditional Independence --- p.88
Chapter 4.2 --- Measuring Conditional Independence --- p.96
Chapter 4.2.1 --- Measuring independence with partial correlation --- p.96
Chapter 4.2.2 --- Measuring independence with mutual information --- p.104
Chapter 4.3 --- Non-Gaussian Distributions and Equivalent Class --- p.108
Chapter 4.4 --- Heuristic CI Tests UnderMonotone Faithfulness Condition --- p.116
Chapter 5 --- Empirical Results of Two-Phase Algorithms --- p.125
Chapter 5.1 --- Experimental Setup --- p.126
Chapter 5.2 --- Structure Error After Each Phase of Two-Phase Algorithms --- p.129
Chapter 5.3 --- Maximal and Average Sizes of Conditioning Sets --- p.131
Chapter 5.4 --- Comparison of the Number of CI Tests Required by Dependency Analysis Approaches --- p.133
Chapter 5.5 --- Reason forWhich Number of CI Tests Required Grow with Sample Size --- p.135
Chapter 5.6 --- Two-Phase Algorithms on Linear Gaussian Data --- p.136
Chapter 5.7 --- Two-phase Algorithms on Linear Non-Gaussian Data --- p.139
Chapter 5.8 --- Compare Two-phase Algorithms with Search-and-Score Algorithms and Lasso Regression --- p.142
Chapter 6 --- Causal Mining in Time Series Data --- p.146
Chapter 6.1 --- A Brief Review of Causation Discovery in Time Series --- p.146
Chapter 6.2 --- Limitations of Constructing SVAR from VAR --- p.150
Chapter 6.3 --- SVAR Being Incapability of Identifying Contemporaneous Causal Order for Gaussian Process --- p.152
Chapter 6.4 --- Estimating the SVARs by Bayesian Network Learning Algorithm --- p.157
Chapter 6.4.1 --- Represent SVARs by Bayesian networks --- p.158
Chapter 6.4.2 --- Getting back SVARs and VARs fromBayesian networks --- p.159
Chapter 6.5 --- Experimental Results --- p.162
Chapter 6.5.1 --- Experiment on artificial data --- p.162
Chapter 6.5.2 --- Application in finance --- p.172
Chapter 6.6 --- Comparison with Related Works --- p.174
Chapter 7 --- Concluding Remarks --- p.178
Bibliography --- p.184
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Gutterman, Craig. "Learning for Network Applications and Control." Thesis, 2021. https://doi.org/10.7916/d8-3bhx-p234.
Full textAbstract:
The emergence of new Internet applications and technologies have resulted in an increased complexity as well as a need for lower latency, higher bandwidth, and increased reliability. This ultimately results in an increased complexity of network operation and management. Manual management is not sufficient to meet these new requirements.
There is a need for data driven techniques to advance from manual management to autonomous management of network systems. One such technique, Machine Learning (ML), can use data to create models from hidden patterns in the data and make autonomous modifications. This approach has shown significant improvements in other domains (e.g., image recognition and natural language processing). The use of ML, along with advances in programmable control of Software- Defined Networks (SDNs), will alleviate manual network intervention and ultimately aid in autonomous network operations. However, realizing a data driven system that can not only understand what is happening in the network but also operate autonomously requires advances in the networking domain, as well as in ML algorithms.
In this thesis, we focus on developing ML-based network architectures and data driven net- working algorithms whose objective is to improve the performance and management of future networks and network applications. We focus on problems spanning across the network protocol stack from the application layer to the physical layer. We design algorithms and architectures that are motivated by measurements and observations in real world or experimental testbeds.
In Part I we focus on the challenge of monitoring and estimating user video quality of experience (QoE) of encrypted video traffic for network operators. We develop a system for REal-time QUality of experience metric detection for Encrypted Traffic, Requet. Requet uses a detection algorithm to identify video and audio chunks from the IP headers of encrypted traffic. Features extracted from the chunk statistics are used as input to a random forest ML model to predict QoE metrics. We evaluate Requet on a YouTube dataset we collected, consisting of diverse video assets delivered over various WiFi and LTE network conditions. We then extend Requet, and present a study on YouTube TV live streaming traffic behavior over WiFi and cellular networks covering a 9-month period. We observed pipelined chunk requests, a reduced buffer capacity, and a more stable chunk duration across various video resolutions compared to prior studies of on-demand streaming services. We develop a YouTube TV analysis tool using chunks statistics detected from the extracted data as input to a ML model to infer user QoE metrics.
In Part II we consider allocating end-to-end resources in cellular networks. Future cellular networks will utilize SDN and Network Function Virtualization (NFV) to offer increased flexibility for network infrastructure operators to utilize network resources. Combining these technologies with real-time network load prediction will enable efficient use of network resources. Specifically, we leverage a type of recurrent neural network, Long Short-Term Memory (LSTM) neural networks, for (i) service specific traffic load prediction for network slicing, and (ii) Baseband Unit (BBU) pool traffic load prediction in a 5G cloud Radio Access Network (RAN). We show that leveraging a system with better accuracy to predict service requirements results in a reduction of operation costs.
We focus on addressing the optical physical layer in Part III. Greater network flexibility through SDN and the growth of high bandwidth services are motivating faster service provisioning and capacity management in the optical layer. These functionalities require increased capacity along with rapid reconfiguration of network resources. Recent advances in optical hardware can enable a dramatic reduction in wavelength provisioning times in optical circuit switched networks. To support such operations, it is imperative to reconfigure the network without causing a drop in service quality to existing users. Therefore, we present a ML system that uses feedforward neural networks to predict the dynamic response of an optically circuit-switched 90-channel multi-hop Reconfigurable Optical Add-Drop Multiplexer (ROADM) network. We show that the trained deep neural network can recommend wavelength assignments for wavelength switching with minimal power excursions. We extend the performance of the ML system by implementing and testing a Hybrid Machine Learning (HML) model, which combines an analytical model with a neural network machine learning model to achieve higher prediction accuracy.
In Part IV, we use a data-driven approach to address the challenge of wireless content delivery in crowded areas. We present the Adaptive Multicast Services (AMuSe) system, whose objective is to enable scalable and adaptive WiFi multicast. Specifically, we develop an algorithm for dynamic selection of a subset of the multicast receivers as feedback nodes. Further, we describe the Multicast Dynamic Rate Adaptation (MuDRA) algorithm that utilizes AMuSe’s feedback to optimally tune the physical layer multicast rate. Our experimental evaluation of MuDRA on the ORBIT testbed shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of nodes while meeting quality requirements. We leverage the lessons learned from AMuSe for WiFi and use order statistics to address the performance issues with LTE evolved Multimedia Broadcast/Multicast Service (eMBMS). We present the Dynamic Monitoring (DyMo) system which provides low-overhead and real-time feedback about eMBMS performance to be used for network optimization. We focus on the Quality of Service (QoS) Evaluation module and develop a Two-step estimation algorithm which can efficiently identify the SNR Threshold as a one time estimation. DyMo significantly outperforms alternative schemes based on the Order-Statistics estimation method which relies on random or periodic sampling.
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Myatt, Emily Laura. "Effect of Learning Preference on Performance in an Online Learning Environment among Nutrition Professionals." Thesis, 2014. http://hdl.handle.net/1805/5516.
Full textAbstract:
Indiana University-Purdue University Indianapolis (IUPUI)Background: Online courses in healthcare programs like Dietetics have increased in availability and popularity. Objective: The purpose of this study was to investigate the connections between online learning environments and Myers-Briggs Type Indicator (MBTI) dimensions among Nutrition Professionals. This research will add to the knowledge base of educators responsible for the design and development of online nutrition courses and will enhance Nutrition Professionals’ academic and professional outcomes. Design: Semi-experimental study design. Subjects/Setting: Thirty-one Nutrition Professionals with mean age of 29 years old. All elements of the study were done online. Statistical Analysis: MBTI dimension summaries were done for descriptive statistics. Fisher’s Exact Test was used to compare frequency of MBTI dimensions in the learning modules (LM) and to analyze learning modality preference based on MBTI dimensions. Two-Sample T-Tests compared test scores for LM groups and test scores for extraverts and introverts. Paired T-Test assessed improvement in test scores related to LM preference. Chi-Square Test compared preferences for the second learning module for both LM groups. Results: The majority of participants’ MBTIs were ESFJ at 35% or ISFJ at 19%. There were more extraverts (71%) compared to introverts (29%). Both LM groups had similar MBTI dimensions. Extraverts and introverts had similar improvements in scores and LM preferences. LM groups performed similarly and in general participants preferred the second learning module they were assigned. Preference for the second LM could be because participants enjoyed the first LM and wanted to learn more information. Both LM groups significantly improved their scores (P=<.0001) in their first and second learning modules regardless of learning module design. Participants were highly motivated to learn as evidenced by their enrollment in this study and completion of 10 hours of learning modules. Motivation to learn may have been the strongest reason performance significantly improved. Conclusion: LM groups significantly improved their LM scores and learned similar amounts. MBTI dimensions extravert and introvert and preferred learning modality had limited impact on performance for this sample of Nutrition Professionals. These results indicate that motivation may be the key to increasing performance in online nutrition courses.
Books on the topic "Internet searching – Statistical methods"
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Digital methods. Cambridge, Massachusetts: The MIT Press, 2013.
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Internet measurement: Infrastructure, traffic, and applications. Chichester, UK: John Wiley & Sons, Ltd, 2007.
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Developments in data extraction, management, and analysis. Hershey, PA: Information Science Reference, 2012.
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Nicola, Pearce-Smith, Heneghan Carl, Perera Rafael, and Badenoch Douglas, eds. Searching skills toolkit: Finding the evidence. Chichester, West Sussex: Wiley Blackwell, 2009.
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L, Givot Danna, ed. Google analytics demystified: A hands-on approach. Place of publication not identified]: Joel J. Davis (printed on-demand), 2015.
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G, Gauch Hugh. Statistical analysis of regional yield trials: AMMI analysis of factorial designs. Amsterdam: Elsevier, 1992.
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A, Reynolds Rodney, Woods Robert 1970-, and Baker Jason D, eds. Handbook of research on electronic surveys and measurements. Hershey, PA: Idea Group Reference, 2007.
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Joe, Teixeira, Tyler Mary E. 1970-, and ebrary Inc, eds. Google Analytics. 3rd ed. Indianapolis, Ind: Wiley Pub., Inc., 2010.
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Sanders, Rob. 42 rules for applying Google Analytics. Cupertino, Calif: Super Star Press, 2012.
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Sams teach yourself Google Analytics in 10 minutes. Indianapolis, Ind: Sams Pub., 2011.
Find full textBook chapters on the topic "Internet searching – Statistical methods"
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Mashhoudy, Houshang. "Individualised Assignments on Modelling Car Prices using Data from the Internet." In Assessment Methods in Statistical Education, 247–57. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470710470.ch21.
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Tsypin, Pavel, Dmitry Macheret, and Nadezhda Valerievna Kapustina. "The Problem of Specific Railway Transport Resources Sharing." In Advances in Business Strategy and Competitive Advantage, 13–27. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-0361-4.ch002.
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The desire of entrepreneurs and consumers to reduce the costs of circulation and purchases led to the development of a new form of business management based on the principles of the sharing economy. This business model is based on the fact that instead of owning certain things (tools, equipment, cars, housing), consumers use them on a rental basis. It is worth noting that this business model can exist and develop only with the use of internet resources and modern information technologies. Thus, the considered business model reduces costs by reducing the cost of searching for information and the speed of the transaction, as well as by eliminating the cost of acquisition and property possession. The aim of the study is to analyze and identify the problems of sharing economic resources and emerging disruptive technologies on the example of transport, especially railway transport. The following methods were used in the research: logical-analytical, statistical, methods of dynamic series analysis, methods of technical and economic calculations, the method of comparisons.
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UZAN, JEAN-PHILIPPE, ROLAND LEHOUCQ, and JEAN-PIERRE LUMINET. "3D STATISTICAL METHODS FOR SEARCHING SPACE TOPOLOGY: WHAT ARE THE LIMITATIONS?" In The Ninth Marcel Grossmann Meeting, 1939–40. World Scientific Publishing Company, 2002. http://dx.doi.org/10.1142/9789812777386_0436.
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Cocco, Simona, Rémi Monasson, and Francesco Zamponi. "High-dimensional inference: searching for principal components." In From Statistical Physics to Data-Driven Modelling, 39–58. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780198864745.003.0003.
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Abstract We have focused so far on how to infer simple models (defined by one or few parameters) from few or many data. In this chapter we are going to address a more complex situation, where the number of unknown parameters is comparable to the number of available data. This situation happens in many practical applications of statistical inference methods. We here concentrate on one of them, principal component analysis (PCA), that is, the inference of the most relevant direction in the high-dimensional space of data. Based on random matrix theory we will see how the inference of this direction is characterized by a phase transition, called retarded learning, which defines a minimum value of the number of data per parameter below which successful inference is not possible.
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Janakova, Milena. "Big Data and Simulations for the Solution of Controversies in Small Businesses." In Encyclopedia of Information Science and Technology, Fourth Edition, 6907–15. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2255-3.ch598.
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The global information society creates data in various formats and data is stored in many sources. Interest is focused on true story formation with respect to sustainable development. The suitable recommendation is to implement a multidimensional view on big data. Such an approach works with big data along three levels. Basic level represents default activities and analyses for data storage in data warehouse. Advanced level is focused on searching for links between stored data and information sources in the global society and variable level searches unexpected events based on complex statistics and mathematical methods with the support of Artificial Intelligence, Business Intelligence, Customer Intelligence, Competitive Intelligence, Swarm Intelligence. These kinds of activities are important for IT product development such as specification of the road for an adopted methodology, definition of a reference for needed dimensions and phases for IT development, and also as a warning against omissions and mistakes.
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Janakova, Milena. "Big Data and Simulations for the Solution of Controversies in Small Businesses." In Advances in Marketing, Customer Relationship Management, and E-Services, 657–67. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7766-9.ch051.
Full textAbstract:
The global information society creates data in various formats, and data is stored in many sources. Interest is focused on true story formation with respect to sustainable development. The suitable recommendation is to implement a multidimensional view on big data. Such an approach works with big data on three levels. The basic level represents default activities and analyses for data storage in data warehouse. The advanced level is focused on searching for links between stored data and information sources in the global society, and variable level searches unexpected events based on complex statistics and mathematical methods with the support of artificial intelligence, business intelligence, customer intelligence, competitive intelligence, swarm intelligence. These kinds of activities are important for IT product development such as specification of the road for an adopted methodology, definition of a reference for needed dimensions and phases for IT development, and also as a warning against omissions and mistakes.
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Chen, Xiaoling, Rohan D. W. Perera, Ziqian (Cecilia) Dong, Rajarathnam Chandramouli, and Koduvayur P. Subbalakshmi. "Deception Detection on the Internet." In Handbook of Research on Computational Forensics, Digital Crime, and Investigation, 334–54. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-836-9.ch014.
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This chapter provides an overview of techniques and tools to detect deception on the Internet. A classification of state-of-the-art hypothesis testing and data mining based deception detection methods are presented. A psycho-linguistics based statistical model for deception detection is also described in detail. Passive and active methods for detecting deception at the application and network layer are discussed. Analysis of the pros and cons of the existing methods is presented. Finally, the inter-play between psychology, linguistics, statistical modeling, network layer information and Internet forensics is discussed along with open research challenges.
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Meena, Yogesh Kumar, and Dinesh Gopalani. "Statistical Features for Extractive Automatic Text Summarization." In Advances in Business Information Systems and Analytics, 126–44. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0293-7.ch008.
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Automatic Text Summarization (ATS) enables users to save their precious time to retrieve their relevant information need while searching voluminous big data. Text summaries are sensitive to scoring methods, as most of the methods requires to weight features for sentence scoring. In this chapter, various statistical features proposed by researchers for extractive automatic text summarization are explored. Features that perform well are termed as best features using ROUGE evaluation measures and used for creating feature combinations. After that, best performing feature combinations are identified. Performance evaluation of best performing feature combinations on short, medium and large size documents is also conducted using same ROUGE performance measures.
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Meena, Yogesh Kumar, and Dinesh Gopalani. "Statistical Features for Extractive Automatic Text Summarization." In Natural Language Processing, 619–37. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0951-7.ch030.
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Automatic Text Summarization (ATS) enables users to save their precious time to retrieve their relevant information need while searching voluminous big data. Text summaries are sensitive to scoring methods, as most of the methods requires to weight features for sentence scoring. In this chapter, various statistical features proposed by researchers for extractive automatic text summarization are explored. Features that perform well are termed as best features using ROUGE evaluation measures and used for creating feature combinations. After that, best performing feature combinations are identified. Performance evaluation of best performing feature combinations on short, medium and large size documents is also conducted using same ROUGE performance measures.
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Saeed, Soobia, N. Z. Jhanjhi, Mehmood Naqvi, Mamoona Humayun, and Vasaki Ponnusamy. "Analyzing the Performance and Efficiency of IT-Compliant Audit Module Using Clustering Methods." In Industrial Internet of Things and Cyber-Physical Systems, 351–76. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2803-7.ch018.
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Human beings have a knack for errors. Counter-effective actions rendered to specify and rectify such errors in a minimum period of time are required when effectiveness and swift advancement depends on the capability of acknowledging the faults and errors and repair quickly. The software as audit module application in IT complaint is in review in this commentary as is another significant instrument created in the field of data analysis that digs deep into quickly and successfully assessing the imprecisions or grievances identified by the users in a certain company. The target of this study is to evaluate the statistical significance in relationship between client reporting attitude and client reliability and to evaluate the impact of strong responsiveness on client reliability, to measure the statistically noteworthy effect of client grievance conduct on service quality, and to test the impact of service quality on client dedication.
Conference papers on the topic "Internet searching – Statistical methods"
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Kozitsyn, Aleksandr Sergeevich, Sergey Alexandrovich Afonin, and Dmitry Alexeevich Shachnev. "Algorithm for Searching Experts in Scientometric Systems." In 23rd Scientific Conference “Scientific Services & Internet – 2021”. Keldysh Institute of Applied Mathematics, 2021. http://dx.doi.org/10.20948/abrau-2021-6-ceur.
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The use of modern methods of thematic analysis for the analytical processing of large amounts of information is currently used in almost all spheres of human activity. Scientometrics is one such area. Research carried out in this area shows that the statistical characteristics of citation rates are highly dependent on the thematic area of papers at hand. In this regard, systems for calculating citation indicators and constructing assessments of the quality of scientific works, ranks of authors or organizations should take into account the thematic area of researchers in order to normalize scientometric indicators. Many scientometric systems and citation systems use subject headings for information retrieval and processing. The world famous citation systems, including WoS, Scopus, Google Shcolar, and others have such headings. Important practical tasks that can be solved using the methods of thematic classification are: assessment of the dynamics of the development of thematic areas in an organization, in a particular country and in world science as a whole; search for articles on a given topic; search and assessment of the authority of experts; search for journals for publication and other urgent tasks. The authors have created software implementations of algorithms for solving some of the listed problems, and research is being conducted to create new effective mathematical models and algorithms in this area.
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Puranen, Juha. "Interactive wiki." In Statistics education for Progress: Youth and Official Statistics. International Association for Statistical Education, 2013. http://dx.doi.org/10.52041/srap.13404.
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Statistical Wikipedia is an excellent source for anyone who is searching information on statistical terms or methods. However it is more like a book than educational material. For a student who wants to learn statistics it can be hard to understand how a statistical method works, when to use it and how to interpret the results. If Wikipedia is made for the student it can be hard to read for an statistician who already knows a lot. Is it possible to increase readability of the pages and add guidance to the pages making them more informative for students?
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Talla Tankam, Narcisse, Janvier Fotsing, Albert Dipanda, and Emmanuel Tonye. "SAR Image Classification Combining Structural and Statistical Methods." In Internet-Based Systems (SITIS 2011). IEEE, 2011. http://dx.doi.org/10.1109/sitis.2011.13.
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Sugawara, Shinji, Hiroyuki Ohnishi, and Yutaka Ishibashi. "Efficient Information Searching Methods Based on User Utility in Super Distributed Environments." In 2008 International Symposium on Applications and the Internet. IEEE, 2008. http://dx.doi.org/10.1109/saint.2008.103.
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Todorov, Konstantin. "Detecting Ontology Mappings via Descriptive Statistical Methods." In 2009 Fourth International Conference on Internet and Web Applications and Services. IEEE, 2009. http://dx.doi.org/10.1109/iciw.2009.33.
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Papadimitriou, Dimitri, and Davide Careglio. "Nonparametric statistical methods to analyze the internet connectivity reliability." In 2015 IEEE International Workshop Technical Committee on Communications Quality and Reliability (CQR 2015). IEEE, 2015. http://dx.doi.org/10.1109/cqr.2015.7129083.
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Yahiaoui, Meriem, Emmanuel Monfrini, and Bernadette Dorizzi. "Implementation of Unsupervised Statistical Methods for Low-Quality Iris Segmentation." In 2014 Tenth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS). IEEE, 2014. http://dx.doi.org/10.1109/sitis.2014.46.
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Ibrahim, Hamza Awad Hamza, Sulaiman Mohd Nor, and Haitham A. Jamil. "Online hybrid internet traffic classification algorithm based on signature statistical and port methods to identify internet applications." In 2013 IEEE International Conference on Control System, Computing and Engineering (ICCSCE). IEEE, 2013. http://dx.doi.org/10.1109/iccsce.2013.6719956.
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Stangl, Dalene. "Design of an internet course for training medical researchers in Bayesian statistical methods." In Training Researchers in the Use if Statistics. International Association for Statistical Education, 2000. http://dx.doi.org/10.52041/srap.00204.
Full textAbstract:
Access to statistical information is at an all-time high, and the information age is fuelling this access at an extraordinary pace. This access increases the capacity for medical researchers to use statistics to guide decision making, yet few courses teach methods to do so. Rarely does statistics training include methods for incorporating statistical output into decision making. Mass education and educational reform is needed. Technological advances of the past decade make this goal possible, and allow us to dramatically change how we use, teach, and think about statistics. This paper covers the conceptual development of an Internet continuing-education course designed to teach the basics the Bayesian statistics to medical researchers. Two questions are discussed: Why the Internet, and why the Bayesian paradigm?
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Jones, Peter, Kay Lipson, and Brian Phillips. "A role for computer intensive methods in introducing statistical inference." In Proceedings of the First Scientific Meeting of the IASE. International Association for Statistical Education, 1993. http://dx.doi.org/10.52041/srap.93311.
Full textAbstract:
Introductory statistics courses have become increasingly prevalent in a wide variety of undergraduate and graduate programs over the past few years. This has resulted in the study of inferential statistics becoming the norm rather than exception. Whilst statistics was once a course chosen by the more mathematically able student, many current students of statistics have little mathematical aptitude or expertise (Tanis, 1992 for example). As a result, many introductory statistic courses have moved away from including much of the statistical theory that underpins inference to become basically technique oriented "recipe book" courses. the internet danger of producing students capable of performing various complex statistical tests without really knowing what they are doing is obvious, particularly if the house includes the use of a sophisticated statistical computer package.
Reports on the topic "Internet searching – Statistical methods"
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Hutchinson, M. L., J. E. L. Corry, and R. H. Madden. A review of the impact of food processing on antimicrobial-resistant bacteria in secondary processed meats and meat products. Food Standards Agency, October 2020. http://dx.doi.org/10.46756/sci.fsa.bxn990.
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For meat and meat products, secondary processes are those that relate to the downstream of the primary chilling of carcasses. Secondary processes include maturation chilling, deboning, portioning, mincing and other operations such as thermal processing (cooking) that create fresh meat, meat preparations and ready-to-eat meat products. This review systematically identified and summarised information relating to antimicrobial resistance (AMR) during the manufacture of secondary processed meatand meat products (SPMMP). Systematic searching of eight literature databases was undertaken and the resultantpapers were appraised for relevance to AMR and SPMMP. Consideration was made that the appraisal scores, undertaken by different reviewers, were consistent. Appraisal reduced the 11,000 initially identified documents to 74, which indicated that literature relating to AMR and SPMMP was not plentiful. A wide range of laboratory methods and breakpoint values (i.e. the concentration of antimicrobial used to assess sensitivity, tolerance or resistance) were used for the isolation of AMR bacteria.The identified papers provided evidence that AMR bacteria could be routinely isolated from SPMMP. There was no evidence that either confirmed or refuted that genetic materials capable of increasing AMR in non-AMR bacteria were present unprotected (i.e. outside of a cell or a capsid) in SPMMP. Statistical analyses were not straightforward because different authors used different laboratory methodologies.However, analyses using antibiotic organised into broadly-related groups indicated that Enterobacteriaceaeresistant to third generation cephalosporins might be an area of upcoming concern in SPMMP. The effective treatment of patients infected with Enterobacteriaceaeresistant to cephalosporins are a known clinical issue. No AMR associations with geography were observed and most of the publications identified tended to be from Europe and the far east.AMR Listeria monocytogenes and lactic acid bacteria could be tolerant to cleaning and disinfection in secondary processing environments. The basis of the tolerance could be genetic (e.g. efflux pumps) or environmental (e.g. biofilm growth). Persistent, plant resident, AMR L. monocytogenes were shown by one study to be the source of final product contamination. 4 AMR genes can be present in bacterial cultures used for the manufacture of fermented SPMMP. Furthermore, there was broad evidence that AMR loci could be transferred during meat fermentation, with refrigeration temperatures curtailing transfer rates. Given the potential for AMR transfer, it may be prudent to advise food business operators (FBOs) to use fermentation starter cultures that are AMR-free or not contained within easily mobilisable genetic elements. Thermal processing was seen to be the only secondary processing stage that served as a critical control point for numbers of AMR bacteria. There were significant linkages between some AMR genes in Salmonella. Quaternary ammonium compound (QAC) resistance genes were associated with copper, tetracycline and sulphonamide resistance by virtue of co-location on the same plasmid. No evidence was found that either supported or refuted that there was any association between AMR genes and genes that encoded an altered stress response or enhanced the survival of AMR bacteria exposed to harmful environmental conditions.