Abstract

The research aims to investigate the private sector attitudes toward operational contracting in special education schools. The research adopted the qualitative approach by using personal interviews with a sample of (45) private school owners and managers in Oman. The results of the research revealed that there is an agreement among the majority of respondents on the ability of the private sector to manage special education schools, the advantages of the partnership, as well as the need for guarantees to support this partnership. The government should fully assume it. The role of the private sector remains to raise the operational efficiency of schools. Opinions vary about the level of powers granted to t

In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

The study aims at knowing the actual uses of instructional technology in teaching history subject in the colleges of education for humanities from the college staff members' perspectives and their attitudes towards it. The sample of the study consisted of (24) instructors from the Colleges of Education for the Humanities, the College of Basic Education- Haditha and the College of Education for Women, the study used the descriptive method, and the questionnaire was consisted of (50) items, and the psychometric properties of the instrument of the study were extracted. The researchers used the appropriate statistical means to analyze the data, and the results of the study showed the following: the teaching staff attitudes towards the use of

Software-Defined Networking (SDN) has evolved network management by detaching the control plane from the data forwarding plane, resulting in unparalleled flexibility and efficiency in network administration. However, the heterogeneity of traffic in SDN presents issues in achieving Quality of Service (QoS) demands and efficiently managing network resources. SDN traffic flows are often divided into elephant flows (EFs) and mice flows (MFs). EFs, which are distinguished by their huge packet sizes and long durations, account for a small amount of total traffic but require disproportionate network resources, thus causing congestion and delays for smaller MFs. MFs, on the other hand, have a short lifetime and are latency-sensitive, but they accou

Asset management involves efficient planning of economic and technical performance characteristics of infrastructure systems. Managing a sewer network requires various types of activities so the network can be able to achieve a certain level of performance. During the lifetime of the network various components will start to deteriorate leading to bad performance and can damage the infrastructure. The main objective of this research is to develop deterioration models to provide an assessment tool for determining the serviceability of the sewer networks in Baghdad city the Zeppelin line was selected as a case study, as well as to give top management authorities the appropriate decision making. Different modeling techniques

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.