Reviewerly/exHarmony huggingface dataset:
Fast Clustering for Massive Collections of Malicious URLs

A large number of network security attacks use the HTTP protocol and rely on malicious URLs. Security solutions can filter such URLs using pattern-based rules, but may also trigger false alerts. Generally, the blocked URLs need to be further analyzed in order to tweak the rules and eliminate the false positives. This analysis is hardened by the large amount of detected URLs.We propose a clustering algorithm that groups together similar URLs, to avoid analyzing small variations of the same data. Further, we propose a method for selecting some representative centroids from each cluster, such that each URL in the cluster is similar with at least a centroid. By employing this method the amount of URLs that need to be analyzed is greatly reduced. The experimental evaluation showed that the algorithm produces quality clusters with a reasonably small running time.
Decision Making System for Determining the Hepatitis Food Criteria using Analytical Hierarchy Process Method

Hepatitis is a kind of inflammation which attacks the body's organ known as liver. Hepatitis itself is divided into commonly known types namely Hepatitis A, B, and C. however, there exist other types of hepatitis called D, E, G which are not familiar. The understanding of patients regarding hepatitis is an obstacle in healing. The thing that is needed is to regulate diet and avoid foods that are prohibited (high sodium, high saturated fat, high sugar, and high protein). Hepatitis sufferers must pay attention to food patterns, must control foods consumed daily, must consume food with low salt, low saturated fat, low in sugar, and low in protein to reduce the risk of not worsening the condition of people with hepatitis. The decision making system determines the hepatitis food criterion using 5 criteria’s, namely the presence of high sodium, high saturated fat, high protein, high sugar, and high iron. While the Analytical Hierarchy Process (AHP) method is a decision making model which defines the multi-factor problems or complex multi criteria into a hierarchy. With hierarchy, a complex problem could be partitioned into smaller groups which are then ordered in a hierarchy to arrange the problem in a structural and systematic way.
Influence of Virtual Storage Controller Type on Microsoft SQL Server 2019 Performance

Influence of different virtual storage controller types on database performance when using VMware virtualization technology has long been debated, but not analyzed properly.In this paper, we're going to analyze the impact of different storage controller types on Microsoft SQL Server 2019 database performance on VMware's vSphere 6.0 hypervisor and try to reach a conclusion as to what's the correct way to design server and virtual machine infrastructure for optimum database performance when using a regular, on-disk database.We will also analyze potential problems that might arise from situations when we migrate from other virtual disk types to paravirtual.
A new model of transformer operation state evaluation based on analytic hierarchy process and association rule mining

In order to establish a transformer state evaluation model for power grid operation and maintenance management, based on the aging mechanism of transformer, a state risk evaluation method based on the Analytic Hierarchy Process (AHP) and the association rule mining is proposed. Based on the big data analysis of the actual state quantity of the transformer, the subjective weight coefficient of different state quantity is determined by the analytic hierarchy process. The objective weight coefficient of the comprehensive state quantity is determined by the association rules mining. And the fusion of the subjective weight coefficient and the objective weight coefficient is completed according to the weight coefficient fusion technology of the mean square deviation method. The practical results show that the model in this paper can evaluate the operation state of transformer comprehensively and accurately.
On Prime Numbers and Related Applications

In this paper we probed some interesting aspects of primorial and factorial primes. We did some numerical analysis about the distribution of prime numbers and tabulated our findings. Also, we pointed out certain interesting facts about the utility value of the study of prime numbers and their distributions in control engineering and Brain networks.
Dynamic Motion Planning for Autonomous Wheeled Robot using Minimum Fuzzy Rule based Controller with Avoidance of Moving Obstacles

In this article, the Minimum Fuzzy Rule-Based (MFRB) sensor-actuator controller has designed for dynamic motion planning of a differential drive wheeled robot among the moving, non-moving obstacles and goal in two-dimensional environments. The ring of ultrasonic sensors and infrared sensors have been attached on the front side, left side, and right side of the wheeled robot, which detects the moving obstacles, as well as non-moving obstacles in any environment. This proposed MFRB sensor-actuator controller helps the wheeled robot to move safely in a different scenario. The onboard sensor interpretation data are fed as input to the MFRB controller, and the MFRB controller provides the Pulse Width Modulation (PWM) based wheel velocity commands to both the left and right motors of a wheeled robot. In the numerical simulation and experiment, we have taken one condition that the speed of wheels of the differential drive wheeled robot is at least more than or equal to the rate of the moving obstacles and the moving goal. The numerical simulations are performed through a MATLAB graphical user interface (GUI), and we have used the differential drive wheeled robot to conduct experiments. The presented numerical simulation and experimental results illustrate that the MFRB controller operated wheeled robot has successfully avoided the stationary and nonstationary obstacles in various scenarios.
Bayesian network algorithms used in the assessment of learners' learning behaviour

In order to solve the problem that teachers cannot monitor learners' learning behaviour or evaluate learners' learning objectively and scientifically because of the relative separation of time and space between teachers and students, covering Bayesian network learning evaluation model based on knowledge relationship is proposed. The information related to students can be divided into two parts: domain-related information and domain-independent information. Firstly, the modelling of domain-related information is mainly discussed. The process of domain-related information modelling is the Bayesian networking process of the courses that students have learned. Secondly, the time and space complexity of the algorithm is reduced by simplifying the network structure and optimising the order of node deletion in the triangulation process. The results show that the model can accurately judge the degree of students' mastery of knowledge, and can provide students with personalised guidance strategy.
The Smart Triad : Big Data Analytics , Cloud Computing and Internet of Things to shape the Smart Home, Smart City, Smart Business &amp; Smart Country

Big data analytics, cloud computing &amp; internet of things are a smart triad which have started shaping our future towards smart home, city, business, country. Internet of things is a convergence of intelligent networks, electronic devices, and cloud computing. The source of big data at different connected electronic devices is stored on cloud server for analytics. Cloud provides the readymade infrastructure, remote processing power to consumers of internet of things. Cloud computing also gives device manufacturers and service providers access to ―advanced analytics and monitoring‖, ―communication between services and devices‖, ―user privacy and security‖. This paper, presents an overview of internet of things, role of cloud computing &amp; big data analytics towards IoT. In this paper IoT enabled automatic irrigation system is proposed that saves data over ―ThingSpeak‖ database an IoT analytics platform through ESP8266 wifi module. This paper also summarizes the application areas and discusses the challenges of IoT.
A Method for Text Data Fragmentation to Provide Security in Cloud Computing

Security is one of the most crucial aspects in cloud computing, in order to provide security in cloud computing there are many cryptographic and non-cryptographic techniques [2][3] are used. Most of the non cryptographic approaches suffer from security breaches and the main drawback of cryptographic algorithms is computation time incurred in encryption and decryption of data. A methodology is proposed to implement unique approach to provide a security in cloud computing. Where text file will be fragmented based on random number generation.From the random number generation algorithm lower range and higher range values will be calculated so that the new random number which needs to compute should be within the lower and higher range of random number.Fragments can be obtained based on the new random number. With reference to the random number, block size or fragment size will be calculated. Hence text file will be divided into fragments.
A novel automatic system for logo-based document image retrieval using hybrid SVDM-DLNN

Many government and private organisations represent themselves to the public using their own symbols or logo which is unique from others so that anyone can easily identify their products or belongings. This gives an ownership and source documentation to the owner by simply providing such logos. Using these logos for document retrieval in the World Wide Web is a booming research in the present era. Since usage of virtual documentation is increased day by day and handling this large data becomes a problem while searching for a single data. In the present research arena, various document image retrieval models are available based on classification and clustering techniques. In this, graph techniques are used to identify the issues in the automatic logo detection model using back propagation neural network along with the single value decomposition model. This proposed research model is concerned about the document retrieval system based on the logo matching process to attain better efficiency and accuracy than the earlier detection models.
A Novel Automatic Journal Recommender System

Recommender Systems (RS) have developed into an important application in several user domains. RS may aid users to discover appropriate items in vast data. The selection of journal publication is generally based on the research domain or topics of document. The traditional method for journal recommendation is carried out by analyzing the document and matching its topics with relavent journal utilizing content-based examination. Though, this approach might create errors because of disparities in manuscript comparisons. In this paper, a novel Jaccard based Journal Finder Neural Network is proposed with pearson correlation coefficient (JJFNN-PC) for journal recommendation. The proposed recommender system allows the researchers to automatically find appropriate publication with journal title and abstract. Similarity coefficient is computed among the journal database and journal title and abstract of user distinctly through Jaccard similarity. The obtained outcome is used for training the novel JFNN that automatically find appropriate publication for user research article. The pearson correlation coefficient is established to validate the correlation between title and abstract of the recommended journal. The experimental result of automatic journal selection process provides the exact journal list and obtained better performance with accuracy of 98.41%.
Analysis and Prediction of the Update of Mobile Android Version

Android fragmentation has been a rising issue for the past decade. Upgrading the version of Androids regularly is highly essential. This would help the Android users across the globe to have an enhanced user-experience and the overall performance is also enhanced. With the escalating cyber-attacks, privacy of data and security becomes highly essential for a friendly Android environment. OEM (Original Equipment Manufacturer) fails to provide the update of Android promptly. Hence different users like Huawei whose chip designers are Qualcomm, One Plus, and other Android users don’t receive the update synchronously. This work focuses on analyzing the data revolving around Android OEMs and the number of days each of the company takes for updating a particular Android version. The data is analyzed considering several factors like the growth of an OEM in releasing the Android updates considering the ratings of the users and days taken to release each version. The prediction is done using Machine Learning algorithms, “Linear regression model,” “Logistic regression” and “Decision Tree,” which helps to precisely know the expected release of the next Android version by a particular OEM and the security fixes. The graphical representations are depicted using R and Python for highly accurate analytical results.
Use of Artificial Intelligence and Automation of Interview Process using the Chat Bot

The AI and the Interview Chat bot used in the system will be the future for any recruitment process as it effectively saves the time /effort and improves the efficiency of the recruitment process. The selection process through the bot will be unbiased and also will be speedy as multiple interviews can be done at the same time. Chatbots will also make the interviewee comfortable as it may be integrated on mobile platform. To summarise, the future of the interviewing process will be made simple by use of the chatbots
Correction: The views, perspectives, and experiences of academic researchers with data sharing and reuse: A meta-synthesis

[This corrects the article DOI: 10.1371/journal.pone.0229182.].
Providing a public auditing cryptographic approach in cloud computing

Cloud computing provides data storage facility to its users in cloud storage servers based on the required payment. Using public auditability, we can check the behaviour of data in the cloud. The auditing protocol must measure less communication cost incurred by the auditor and the cloud server. Third party auditor is responsible for the authentication of secret files in cloud system on behalf of the data owner. This paper describes an auditing system for secure cloud storage systems using privacy preservation scheme. The data auditability technique allows the user to make the data integrity check using a third party. The public auditability system permits the TPA to check the cloud information without downloading the original data from the user. This process involves profiling the data and evaluating the impact of inadequate quality data which results in the performance of the organisation.
iCampusGuide: a multi-purpose guide system in intelligent campus

As an important application of intelligent campus, campus guide aims to help visitors get to the destination. In this paper, a flexible and low-cost campus guide model named iCampusGuide is proposed, which generalises the problem of university campus guide including objectives, constraints, system and algorithms. The proposed iCampusGuide provides visiting reservation, route navigation, parking guideline and broadcasting introduction of buildings during the navigation. Technically, iCampusGuide adopts ibeacons for accurate locating and navigation, provides the parking suggestion by sending real-time snapshots from the parking lot nearest to the destination. Particularly, iCampusGuide provides business mode, tour mode, driving mode, walking mode for different purposes. Each mode uses different route navigation algorithms. To verify the model, a client-server software is developed and implemented in a real university campus. Experiments show that the model is effective.
Virtual Currency and Its Importance in Today's Digitized Society

As a result of the globalization process, online trading is becoming increasingly popular. An importantphenomenon of the present day has therefore become a virtual currency as a possible means of payment or theunderlying instrument of online trading. For this reason, the issue of virtual currency has become the subject of ourresearch. The virtual currency can be considered as a perspective tool of the modern economic practice. Virtualcurrency serves for prompt, simple and safe payment for goods, products and services to the subject that accepts thevirtual currency. The aim of the submitted contribution is to clarify the essence, importance, role, valuation of thevirtual currency in the present digitized society with the discovery and subsequent presentation of potential benefits,respectively. Disadvantages of using this virtual payment. Our intention is to bring a comprehensive view of this issuenot only from the accounting point of view, but also from the auditor's point of view, thus reducing the entropy andfear of interest groups from the innovations of contemporary modern virtual economic practice.
Multi-Phase Digital Authentication of e-Certificate with Secure Concealment of Multiple Secret Copyright Signatures

The work suggests a unique data security protocol for trusted online validation of e-documents like university certificates to confirm its credibility on different aspects. The idea reliably validates such e-documents from both the issuing authority and incumbent perspectives by strongly complying the security challenges like authentication, confidentiality, integrity and non-repudiations. At the very beginning, the parent institute physically issues the client copyright signature to the incumbent and stores this signature and biometric fingerprint of the incumbent on the server database. Additionally, the server secretly fabricates ownership signatures of parent institute and concern officer both within the e-document and this certified e-document is kept on the server database. Importantly, these signature fabrications are governed by self-defined hash computations on incumbent registration and certificate number respectively. Next, the server transmits this signed e-document to the client after a successful login by the client. Now client conceals shared copyright signature and taken thumb impression of the incumbent separately within this received e-document. Critically, these client-side signature castings are employed through self-defined hash computations on the incumbent name and obtained marks respectively. Finally, this authenticated e-document is validated at the server end by sensing all authentic signatures from it through those same identical hash operations. For stronger authenticity each signature is concealed by tracing its valid or authentic circular orientation of fragment sequences and embedding locations both derived from respective hash operations. Also, each signature is dispersed in non-overlapping manners on each separate region of the e-document promoting better signature recovery. Additional robustness is further injected with variable encoding of signature bits on different transformed pixel byte components of the e-Certificate image. Overall, the scheme confirms significant performance enhancements over exiting approaches with exhaustive simulation results on image data hiding aspects and their standardized comparisons
A LINGUISTIC STUDY OF MANIPULATIVE ADVERTISING STRATEGIES OF THE MOBILE NETWORK OPERATORS IN EGYPT AND THE UNITED STATES. COMPARATIVE APPROACH.

Advertising nowadays penetrates all aspects of our daily life: on TV, the radio, in the newspapers, in the mailboxes, on the side of underground metro, etc. Whether advertising is annoying or amusing, useful or misleading, it is a form of communication whereby advertisers communicate the value of a product or service to customers. However, advertising is far from just being informative in an innocent and straightforward way. Advertising has an agenda. It is a skillfully constructed message, which manipulates the viewers’ culturally created perceptions and aspirations, and which presents the advertised product as a way to satisfy the audience’s desires. This happens by creating a specific image for the advertised stuff and building the viewers’ perception of such ads. Advertising is also about establishing a relationship between the advertiser and the viewer and it is important to look at this relationship as it helps to form the consumers’ behavior towards the advertised product. Academic contributions on the linguistic features of advertising appeared few decades and developed into a rich interdisciplinary field of study. Advertising has attracted consistent and intense attention across academic disciplines including marketing, media studies, psychology, sociology, and linguistics. From a linguistic dimension, advertising research focused heavily on the description of specific textual devices or the relations between text and image, and certain pragmatic features, which view advertising as a special concept of discourse. In this sense some important questions remain unapproached, like, how are the addressees motivated to tackle and process linguistic notions in advertising and what are the strategies to manipulate their mental concepts.
Can Time Pressure and Personality Make any Sense together in Software Engineering?

Nowadays, software development failure has become a very serious problem. Inaccurate time estimation is one of the major causes of the software development failure. Inaccurate time estimation mostly creates time pressure that causes several negative impacts on software developers’ mental and physical health. The past studies had also believed that burnouts and job turnover problems happened due to time pressure. Therefore, the objective of this study is to explore time pressure with human behavior to see if they can make any relation. By this way, one can explore the hidden patterns between time pressure and human behavior in software engineering. In order to carry out the study, personality and time pressure studies are explored in general to see if past studies had ever made any space for software domain. Moreover, based on the limited selected studies, the literature review identifies that several authors had correlated the time pressure with personality. Unfortunately, time pressure and software developer personality are not specifically studied together in software engineering. For that reason, this study leaves some recommendations for researchers to contribute in the very topic to make software development better.
Hyper-Scalable JSQ with Sparse Feedback

Load balancing algorithms play a vital role in enhancing performance in data centers and cloud networks. Due to the massive size of these systems, scalability challenges, and especially the communication overhead associated with load balancing mechanisms, have emerged as major concerns. Motivated by these issues, we introduce and analyze a novel class of load balancing schemes where the various servers provide occasional queue updates to guide the load assignment. We show that the proposed schemes strongly outperform JSQ(d) strategies with comparable communication overhead per job, and can achieve a vanishing waiting time in the many-server limit with just one message per job, just like the popular JIQ scheme. The proposed schemes are particularly geared however towards the sparse feedback regime with less than one message per job, where they outperform corresponding sparsified JIQ versions. We investigate fluid limits for synchronous updates as well as asynchronous exponential update intervals. The fixed point of the fluid limit is identified in the latter case, and used to derive the queue length distribution. We also demonstrate that in the ultralow feedback regime the mean stationary waiting time tends to a constant in the synchronous case, but grows without bound in the asynchronous case.