1,720,963 research outputs found
nformation Retrieval: An Overview .* and Awodele Oludele
Full text linkInformation retrieval (IR) is the field of computer science that deals with the processing of documents containing free text, so that they can be rapidly retrieved based on keywords specified in a user's query. IR was born in the 1950s out of necessity to find useful information from large collections. Over the last sixty years, the field has matured considerably. IR technology is the basis of Web-based search engines, and plays a vital role in research, because it is the foundation of software that supports literature search. Several IR systems are used on an everyday basis by a wide variety of users. This article is a brief overview of Information Retrieval
Detection and Mitigation of Known and Unknown DDoS Attacks on Advanced Metering Infrastructure Systems in Nigeria Using Hybrid Machine Learning (Ai) Techniques
Full text linkThe enormous rise of network traffic and its diversity on the Internet have posed new and serious obstacles for detecting network attack activity. Distributed denial of service (DDoS) attack is designed to restrict genuine users from accessing a service for an extended period of time. In this attack, the attacker attempts to compromise a large number of hosts to transmit a large volume of traffic to genuine users. Detecting DDoS attacks is difficult and complicated, primarily different DDoS attacks do not common characteristics through which they can be detected. DDoS attacks are very difficult to fight or trace due to their distributed nature, and automated software tools for conducting DDoS attacks are freely available. This paper proposed a DDoS detection model based on hybrid machine learning technique on AMI systems in the Nigeria Utility Business. It has been discovered that detecting unknown DDoS attacks is difficult to analyze as sometimes the IP packets and header are encrypted. This study proposed a combination of Support Vector Machine (SVM) and Artificial Neural Network (ANN) to detect unknown attacks. The AES 256 algorithm has been employed to decrypt the encrypted IP header. Keywords: ANN, SVM, DDoS attack, AES algorithm, AMI DOI: 10.7176/NCS/13-04 Publication date:May 31st 2022
Voice Activity Detection: Fusion of Time and Frequency Domain Features with A SVM Classifier
Full text linkVoice activity detection (VAD) discriminates between segments of an audio signal that has speech content from the ones with either noise or silence. It is deployed as the front-end of some speech processing applications such as voice recognition, and speaker recognition to improve their performance in terms of accuracy and efficiency. It is also used in the communication system to bring about efficient utilization of transmission bandwidth by ensuring only segments of the audio signal with voice activity are encoded and transmitted. In this work, the VAD algorithm was implemented using a features-fusion strategy. In the pre-processing stage, contents outside the human auditory frequency range were removed with the aid of a digital Butterworth bandpass filter. The signal was then fragmented into frames from where time-domain features (zero-crossing, standard deviation, normalized envelope, kurtosis, skewness, and root-mean-square energy.) and frequency-domain features (13MFCCs) were extracted and then combined to form a feature representation of each frame. Recursive feature elimination was applied to the dataset to reduce the features to seven (7) which was used to train a Support Vector Machine (SVM) to be able to distinguish between voiced and unvoiced frames. A State-of-art performance was recorded by this simple SVM-based VAD system with an accuracy of 100%, recall of 100%, precision of 100% and F1 score of 100% which is at par with similar implementations which utilizes a complex architecture of deep neural network with high computational cost and training time. Keywords: Voice activity detection, fusion strategy, support vector machine, frequency domain features, time domain features DOI: 10.7176/CEIS/13-3-03 Publication date:May 31st 2022
An Enhanced Mobile Financial Security System using Facial Recognition and Resident Token generator
Full text linkA mobile application has been embraced over the years by various sectors of the economy for its ease and controlling power in communication, academics, social platforms, shopping, and financial services like banking. It has also been used to control residential gadgets connected through home networks from mobile smartphones. In the medical sector, it is being used for the retrieval of patient history to make medical resolutions. However, this developed application also poses a threat when not properly implemented or built, as interesting as it seems, it also has its cons, particularly in the financial industry that has embraced mobile banking. The challenges of the mobile app include having a single device with single authentication and authorization poses security issues and can be porous to attacks while some use SMS for token information which is also susceptible to spoofing attacks. The study aims to develop a facial recognition enabled mobile app authentication during the process of logging on a single device using a resident token generator enabled for authorization of transactions on the same banking app. The implementation of the token resident generator icon will be resident on the mobile app where Pin and generated token are used for approvals of banking transactions. Keywords:Authorization, Authentication, Financial security, Two-factor authentication, Resident Token generator, Facial recognition, Mobile app DOI: 10.7176/CEIS/13-3-02 Publication date:May 31st 202
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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