The study aimed to reveal the role of social capital represented by its dimensions (structural, relational, and cognitive) in strengthening the management of excellence in Azadi Hospital / Duhok. In order to reach the goal of the study, the study variables were highlighted in theory through framing concepts and literary contributions for researchers in this field, In the field, the questionnaire was used as a basic tool to collect data from the individuals in the research sample who were represented by officials and individuals working from administrators and technicians, as (120) forms were distributed to the respondents, and (110) were retrieved from them in a way that is valid for analysis. Several statistical methods have bee

The experiment was conducted at the Faculty of Agriculture University of Ain Shams-Egypt, from January to March 2008, to study the effect of different levels of chromium yeast (Cr-yeast) on broiler chickens performance, carcass quality and enzyme activity through 35 days of experimental periods. A total of 450 one-day old unsexed chickens (Cobb) strain were used. The birds were randomly allocated to five treatments with 3 replicates each. The treatments were control (T1) without supplementation and T2, T3, T4 and T5 which were supplemented with 0.5, 1, 1.5 and 2 mg Cr-yeast /kg diet, respectively. Live body weight and weight gain were significantly (p<0.05) higher when Cr-yeast were supplemented at 1 (T3), 1.5 (T4) and 2 (T5) mg/kg diet. Fe

This investigation showed (31) species belonging to (15) genera under (five) families and two orders. The leafminers Dipter families (Agromozidae, Anthomyiidae, Drosophilidae), Agromyzid flies is the highest level of investigated many host plants, but other families have lowest host plants. The synonyms of species were provided from GBIF scarlet's. The date and localities of sampling collection were recorded.

Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

The pumping station became widely used in many fields. Free surface vortices at intakes of pumps are not favorable. It may cause noise, excessive vibration, damage to the pumping structure, reduction in efficiency and flow for hydro-turbines, etc. One of the important problems encountered during the pump intake design is the depth of submergence and other design parameters to avoid strong free-surface vortices formation. This study aims to compute the critical submergence depth with some geometrical and hydraulic limitations by using Computational Fluid Dynamic (CFD) package. The mathematical model was validated with a laboratory model that had been conducted. The model of three intake pipes was investigated under five d

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa