Face detection systems are based on the assumption that each individual has a unique face structure and that computerized face matching is possible using facial symmetry. Face recognition technology has been employed for security purposes in many organizations and businesses throughout the world. This research examines the classifications in machine learning approaches using feature extraction for the facial image detection system. Due to its high level of accuracy and speed, the Viola-Jones method is utilized for facial detection using the MUCT database. The LDA feature extraction method is applied as an input to three algorithms of machine learning approaches, which are the J48, OneR, and JRip classifiers.  The experiment’s

ABSTRACT Background: Bracket rebonding is a common problem in orthodontics which may result in many drawbacks. The aims of this study were to evaluate the effects of application of two enamel protective agents “Icon” and “ProSeal” on shear bond strength before and after rebonding of stainless steel orthodontic brackets using conventional orthodontic adhesive and to assess the site of bond failure. Materials and methods: Fifty sound extracted human upper first premolar teeth were selected and randomly divided into two equal groups; the first time bonding and the rebonding groups (n=30). Each group was subdivided into control, Icon and ProSeal subgroups. The enamel protective agents were applied after etching (precondi

Background: The present study was carried out to compare shear bond strength of sapphire bracket bonded to zirconium surface after using different methods of surface conditioning and assessment of the adhesive remnant index. Materials and methods: The sample composed of 40 zirconium specimens divided into four groups; the first group was the control, the second group was conditioned by sandblast with aluminum oxide particle 50 μm, the third and fourth group was treated by (Nd: YAG) laser (1064nm)(0.888 Watt for 5 seconds) for the 1st laser group and (0.444 Watt for 10 seconds) for the 2nd laser group. All samples were coated by z-prime plus primer. A central incisor sapphire bracket was bonded to all samples with light cure adhesive res

Thermomechanical analysis (TMA) and differential scanning calorimetry (DSC) are used to investigate the effect of molding and annealing of polyester on the behavior of thermal expansion and crystallization since these factors play role in the reprocessing or recycling of the polymer. The dynamic mode of the TMA provides enhanced characterization information about the polyester since it separates the transitions into reversible and irreversible signals, and also reveals the progress of the amorphous regions as the polyester loses strength with the increasing temperature approaching melting. Slow cooling after annealing brings crystallization that may be attributed to molecular chain straightening due to orientation.

This study focused on the biological synthesis of silver nanoparticles (AgNPs), using prodigiosin pigment produced by Serratia marcescens. The effect of parameters such as pH, temperature, time, with various concentrations of silver nitrate (AgNO₃) and prodigiosin on the synthesis of AgNPs were also studied.  Optimized results of the biosynthesis process revealed an increase in the intensity of Surface Plasmon Resonance (SPR) bands of nanoparticles with shifting at the wavelength of 400 nm. In addition, optimum synthesis of AgNPs was achieved at pH 12, temperature 55℃, and reaction time 24 h, with concentrations of prodigiosin, as a reducing agent, of 12.5 µg/ml and silver ion concentration of 1 mM. Measuremen

      Information centric networking (ICN) is the next generation of internet architecture with its ability to provide in-network caching that make users retrieve their data efficiently regardless of their location. In ICN, security is applied to data itself rather than communication channels or devices. In-network caches are vulnerable to many types of attacks, such as cache poisoning attacks, cache privacy attacks, and cache pollution attacks (CPA). An attacker floods non-popular content to the network and makes the caches evict popular ones. As a result, the cache hit ratio for legitimate users will suffer from a performance degradation and an increase in the content’s retrieval latency. In this paper, a popularity variation me

Type-1 diabetes is defined as destruction of pancreatic beta cell, virus and bacteria are some environmental factor for this disease. The study included 25 patients with type-1 diabetes mellitus aged between 8 – 25 years from Baghdad hospital and 20 healthy persons as control group. Anti-rubella IgG and IgM, anti-Chlamydia pneumonia IgG and IgM were measured by ELISA technique while anti-CMV antibody were measured by immunofluorescence technique. The aim of current study was to know the trigger factor for type-1 diabetes. There were significant differences (P<0.05) between studied groups according to parameters and the results lead to suggest that Chlamydia pneumonia, CMV and rubella virus may trigger type-1 diabetes mellitus in Iraqi pat

In this study negative result of real-time reverse transcription-QPCR (RT-PCR) assay
tests of Influenza virus of nasal screetion and throat swap samples of Iraqi patients
hospitalized with signs and symptoms of an upper respiratory tract infection in Central
Republic Health Laboratory in Iraq were tested for Respiratory Syncytial Virus
infection by RT PCR .Positive samples was 4 out 0f 20 were used .Viral isolation was
done on a monolayer of 70-80% confluent Human Lung Carcinoma Cells (A549) cell
line and incubated at 33ºC for 4 days .Syncytia was observed in 3 positive samples.

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices