Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

Objectives: Small field of view gamma detection and imaging technologies for monitoring in vivo tracer uptake are rapidly expanding and being introduced for bed-side imaging and image guided surgical procedures. The Hybrid Gamma Camera (HGC) has been developed to enhance the localization of targeted radiopharmaceuticals during surgical procedures; for example in sentinel lymph node (SLN) biopsies and for bed-side imaging in procedures such as lacrimal drainage imaging and thyroid scanning. In this study, a prototype anthropomorphic head and neck phantom has been designed, constructed, and evaluated using representative modelled medical scenarios to study the capability of the HGC to detect SLNs and image small organs. Methods: An anthropom

The aim of this study is to evaluate the anti fungal activity of a combination of essential oils against water molds. HPLC analysis was done to evaluate the quantity and quality of the active compounds in this combination which extracted from three herbs( Peppermint Menthapiperita ,Thyme Thymusvulgaris, Common sage Salvia officinalis L.) and the active compounds are Camphor,Menthol,,Thujone and Thymol with different concentrations. In this study (MIC) , (MFC) were measured and (LD50) determined after 48,96 h from fingerlings treatment of common carp in aquariums .The results of (MIC) were 0.025µl/ml for Aphanomyces sp. and 0.015µl/ml for both Achlya sp. and Fusariumsolani which showed significant differences(p<0.05) from Malachite gre

Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and

Routing is the process of delivering a packet from a source to a destination in the network using a routing algorithm that tries to create an efficient path. The path should be created with minimum overhead and bandwidth consumption. In literature, routing protocols in VANET were categorized in many ways, according to different aspects. In the present study, we prefer the classification based on the number of hops to reach the destination node. In literature, these are single-hop and multi-hops protocols. We first discuss the two types and then compare the MDDV (multi-hops protocol) with VADD (single-hop protocol). The comparison is theoretically and experimentally implemented by providing a network environment consisting of SUMO, VIENS and

ABSTRUCT

In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

This research concerns the fact of the school garden and how can we tackle this issue. The research starts with a question forwarded to those who are interested in the ministry of education matters; the question is that how is the extent of interest in the school garden project? And how it is activated in the Iraqi Educational Institution program? In addition, the analysis reveals the importance of the school garden since we, as teachers and students, suffer from seeing the view of the trashes, the wastes of school furniture, the stinking water and the weeds and how it is accumulated in the back yard of the school. To add fuel to the fire, the increase in number of the students; year after year. This increase leads to adding more classes