Search results for "Machine"

Role of coefficient of thermal expansion on bond strength of ceramic veneered yttrium-stabilized zirconia

2017

Background Incompatible coefficient of thermal expansion (CTE) is supposed to be a reason for chipping of ceramic veneered zirconia. This study evaluates the effect of veneering ceramic at varied CTE on bond strength to zirconia. Material and Methods Zirconia disks (Z, O 10 mm, 1.0 mm thickness) were prepared from Y-TZP (Cercon®) and sintered at 1350°C for 6 hours. All zirconia disks were veneered with ceramics ((O 7.0 mm, 1.5 mm thickness) with varied CTE including VITADur® alpha (VDα), VITAVM®7 (VM7), VITAVM®9 (VM9), Cercon® ceramkiss (CCK), IPSe.max® ceram (IeC), and IPS dSIGN® (IdS) (n=15). The specimens were thermo-cycled (5-55 °C, 500 cycles) prior to determine the shear bond strength…

Effect of different sintering process on flexural strength of translucency monolithic zirconia

2018

Background Sintering process is responsible for the strength of zirconia restoration. This study evaluated the effect of different sintering temperatures and sintered-holding times on flexural strength of translucency monolithic zirconia. Material and Methods One hundred and thirty five zirconia bar specimens (width-length-thickness = 10×20×1.5 mm) were prepared from yttria-stabilized tetragonal zirconia polycrystalline (Y-TZP) ceramic and randomly divided into nine groups to be sintered at different temperatures [decreasing- (SD, 1350°C), regular- (SR, 1450°C), and increasing- (SI, 1550°C) sintering temperature] and different sintered-holding times [shortening- (HS, 60 min), regular- (HR, …

Fracture resistance of roots filled with three different obturation techniques

2012

Objectives: The aim of this study was to compare in vitro root fracture resistance following root canal filling with AH 26 using lateral condensation, BeeFill, and Thermafil techniques. Study Design: Eighty extracted human mandibular premolars with similar dimensions were selected. In order to standardize the roots, measurements were taken in two separate regions of the teeth—at the cemento-enamel junction and 8 mm apically from the junction—buccolingual as well as mesiodistal for every tooth. Teeth were then randomly divided into five groups (n=16). With the exception of the non-prepared group (Group 1), instrumentation was done in all groups. In group 2, instrumentation but no filling was…

Influence of artificial aging and ZrO2 nanoparticle-reinforced repair resin on the denture repair strength

2019

Background The purpose of this study was to evaluate the effect of aging process on the tensile strength (TS) of repaired acrylic denture base using ZrO2 nanoparticles (nano-ZrO2)-reinforced autopolymerized resin. Material and Methods A total of 240 heat-polymerized acrylic resin specimens (n=10) were prepared and sectioned creating 2 mm-repair-gap. Autopolymerized acrylic resin, pure and modified with 2.5, 5, and 7.5wt% nano-ZrO2 were used for specimens repair. TS of repaired specimens were measured using the universal testing machine after water immersion at 37oC for 2, 7 and 30 days. At each time interval, half the immersed specimens underwent thermo-cycling aging process (5000 cycles at…

Intruder Pattern Identification

2008

This paper considers the problem of intrusion detection in information systems as a classification problem. In particular the case of masquerader is treated. This kind of intrusion is one of the more difficult to discover because it may attack already open user sessions. Moreover, this problem is complex because of the large variability of user models and the lack of available data for the learning purpose. Here, flexible and robust similarity measures, suitable also for non-numeric data, are defined, they will be incorporated on a one-class training K N N and compared with several classification methods proposed in the literature using the Masquerading User Data set (www.schonlau.net) repr…

Bot recognition in a Web store: An approach based on unsupervised learning

2020

Abstract Web traffic on e-business sites is increasingly dominated by artificial agents (Web bots) which pose a threat to the website security, privacy, and performance. To develop efficient bot detection methods and discover reliable e-customer behavioural patterns, the accurate separation of traffic generated by legitimate users and Web bots is necessary. This paper proposes a machine learning solution to the problem of bot and human session classification, with a specific application to e-commerce. The approach studied in this work explores the use of unsupervised learning (k-means and Graded Possibilistic c-Means), followed by supervised labelling of clusters, a generative learning stra…

A Gamified Mobility Experience

2020

We believe in the use of urban games to define new enjoyable experiences, change citizens’ unsustainable habits and educate them to new environment-and social-friendly ones. This paper presents MUV, an innovative action that has the power to engage citizens and foster sustainable mobility behaviors. MUV complements engaging HMIs with a participatory method within an iterative innovation process called the virtuous cycle (understand, involve, co-create, implement, experiment). The innovation process has led to a new game dynamic: Mobility as a Sport. It results in a rewarding personal mobility experience; the same rewarding sensations the athletes feel when they improve their results.

Prediction of user action in moving-target selection tasks

2015

Selection of moving targets is a common, yet complex task in human–computer interaction (HCI), and more specifically in virtual reality (VR). Action prediction has proven to be the most comprehensive enhancement to address moving-target selection challenges. Current predictive techniques, however, heavily rely on continuous tracking of user actions, without considering the possibility that target-reaching actions may have a dominant pre-programmed component—this theory is known as the pre-programmed control theory.Thus, based on the pre-programmed control theory, this research explores the possibility of predicting moving-target selection prior to action execution. Specifically, three level…

2021

In COVID-19 related infodemic, social media becomes a medium for wrongdoers to spread rumors, fake news, hoaxes, conspiracies, astroturf memes, clickbait, satire, smear campaigns, and other forms of deception. It puts a tremendous strain on society by damaging reputation, public trust, freedom of expression, journalism, justice, truth, and democracy. Therefore, it is of paramount importance to detect and contain unreliable information. Multiple techniques have been proposed to detect fake news propagation in tweets based on tweets content, propagation on the network of users, and the profile of the news generators. Generating human-like content allows deceiving content-based methods. Networ…

Extracting Features from Social Media Networks Using Semantics

2016

This paper focuses on the analysis of social media content generated by social networks (e.g. Twitter) in order to extract semantic features. By using text categorization to sort text feeds into categories of similar feeds, it has been proved to reduce the overhead that is required to retrieve these feeds and at the same time, it provides smaller pools in which further investigations can be made easier. The aim of this survey is to draw a user profile, by analysing his or her tweets. In this early stage of research, being a pre-processing phase, a dictionary based approach is considered. Moreover, the paper describes an algorithm used in analysing the text and its preliminary results. This …