This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi

  Many managers in geometrical and technical organizations prefer to deal with quantitative values ​​to choose between the available options and choose the best alternative to avoid randomization and bias in decision making. One of them Baghdad Water Department, which seeks to develop the quality of its product (drinking water) and achieve its objectives under increasing growing population and the demand for water, Some of TQM tools, especially the statistical, have this ability because there is chance to use historical data and experiment of employees in Application . Two statistical tools were applied: the nominal group technique, matrix data analysis technique as well as the brainstorming tool to search for the best o

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

Fatty Acid Methyl Ester (FAME) produced from biomass offers several advantages such as renewability and sustainability. The typical production process of FAME is accompanied by various impurities such as alcohol, soap, glycerol, and the spent catalyst. Therefore, the most challenging part of the FAME production is the purification process. In this work, a novel application of bulk liquid membrane (BLM) developed from conventional solvent extraction methods was investigated for the removal of glycerol from FAME. The extraction and stripping processes are combined into a single system, allowing for simultaneous solvent recovery whereby low-cost quaternary ammonium salt-glycerol-based deep eutectic solvent (DES) is used as the membrane phase.

Objectives: The study aims to evaluate effectiveness of health education program on health care providers’ knowledge toward immunization of children at primary health care centers in Kirkuk city.

Methodology: A quasi –experimental study design two- group (pre-test, post-test 1 and post-test 2) conducted at primary health care centers in Kirkuk city during the period from 28 October 2019 to 10 August 2020. By collecting (50) samples divided into two groups, each one (25) participant as control & study group. The study group exposed to the education program only.

Results: Results showed a clear positive