Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

Objective(s): The world of dentistry is constantly evolving, and with the advent of 3D printing technology, the possibilities are endless. However, little is known about the effects of adding ZrO2 NPs to the denture base resin of 3D additive manufacturing technique.Aim of this study is to evaluate the behavior of resin which is used to 3D printing of denture base with the addition of ZrO2 NPs on denture adaptation property and diametral compression strength.Methods: 60 samples were printed, 30 disks for diametral compressive test and 30 denture base for denture adaptation test. Three groups per test (n=10). The control group for each test included unreinforced 3Dprinted denture base resin, and the other groups were  reinforced with (2&

Abstract: Objectives: To investigate the effect of temperature elevation on the bonding strength of resin cement to the zirconia ceramic using fractional CO2 laser. Background: Fractional CO2 laser is an effective surface treatment of zirconia ceramic, as it increases the bonding strength of zirconia to resin cement. Methods: Thirty sintered zirconia discs (10 mm diameter, 2 mm thickness) were prepared and divided to three groups (N=10) and five diffident pulse durations were used in each group (0.1, 0.5, 1, 5 and 10 ms). Group A was treated with 10 W power setting, group B with 20 W and group C with 30 W. During laser irradiation, temperature elevation measurement was recorded for each specimen. Luting cement was bonded to the treated z

In current study a computation fluid dynamic (CFD) technique was used to investigate the effect of groynes shape and spacing on the scour pattern and the maximum scour depth in open channel flow. CFD model have been validated throughout comparing the numerical results with three previous experimental studies for a single groyne located in open channel with three different shapes (L, quadrant, and parabola shapes). The comparison revealed very good agreement between numerical results of the maximum scour depth with the results of all experimental models. Moreover, investigations of the effect of multi-groynes (three groynes and four groynes) arranged in parallel with constant spacing and also with variable spacing have been done, the

Background: The bond strength of root canal sealers to dentin was important for maintaining the integrity of the seal in root canal filling in both static and dynamic situations. In a static situation, it should eliminate any space that allowed the percolation of fluids between the filling and the wall while in a dynamic situation; it was needed to resist dislodgement of the filling during subsequent manipulation. Materials and Methods: Forty mandibular premolars were selected for this study. All canals were instrumented using ProTaper rotary instruments. Instrumentation was done with copious irrigation of 5.25% sodium hypochlorite. Roots were randomly divided into four groups according to the type of cleaning and method of root canal irrig

In this study, the spreading of the pandemic coronavirus disease (COVID-19) is formulated mathematically. The objective of this study is to stop or slow the spread of COVID-19. In fact, to stop the spread of COVID-19, the vaccine of the disease is needed. However, in the absence of the vaccine, people must have to obey curfew and social distancing and follow the media alert coverage rule. In order to maintain these alternative factors, we must obey the modeling rule. Therefore, the impact of curfew, media alert coverage, and social distance between the individuals on the outbreak of disease is considered. Five ordinary differential equations of the first-order are used to represent the model. The solution properties of the system ar

     The earth's surface comprises different kinds of land cover, water resources, and soil, which create environmental factors for varied animals, plants, and humans. Knowing the significant effects of land cover is crucial for long-term development, climate change modeling, and preserving ecosystems. In this research, the Google Earth Engine platform and freely available Landsat imagery were used to investigate the impact of the expansion and degradation in urbanized areas, watersheds, and vegetative cover on the land surface temperature in Baghdad from 2004 to 2021. Land cover indices such as the Normalized Difference Vegetation Index, Normalized Difference Water Index, and Normalized Difference Built-up Index (NDVI, NDWI, an