Background: Skull secondary tumors are malignant bone tumors which are increasing in incidence.Objective: The objectives of this study were to present clinical features , asses the outcome of patients with secondary skull tumors ,characterize the MRI features, locations, and extent of secondary skull tumors to determine the frequency of the symptomatic disease.Type of the study: This is a prospective study.Methods: This is a prospective study from February 2000 to February 2008. The patients were selected from five neurosurgical centers and one oncology hospital in Baghdad/Iraq. The inclusion criteria were MRI study of the head(either as an initial radiological study or following head CT scan when secondary brain tumor is suspected , visible or palpabable skull mass is noted ) that revealed either calvarial or skull base metastases were included in this study.Results: During the period of the study 175 patients were included according the inclusion criteria. Primary sites were breast cancer (54.85%), lung cancer (14.28%), prostate cancer (6.28%), malignant lymphoma (5.14%), and others (19.42%). The mean time from primary diagnosis to skull metastasis diagnosis was 71 months for cases of breast cancer, 26 months for prostate cancer, 9 months for lung cancer, and 4 months for malignant lymphoma. Calvarial circumscribed intraosseous metastases were found most frequently (25.7%). The patients were mainly asymptomatic. However, some patients suffered from local pain or cranial nerve palsies that harmed their quality of life. Treatment, mainly for symptomatic cases, was by local or whole-skull irradiation.Conclusion: Secondary skull tumors are not rare, and most are calvarial circumscribed intraosseous tumors. MRI contribute to understanding their type, location, and multiplicity, and their relationship to the brain, cranial nerves, and dural sinuses. Radiation therapy improved the quality of life (QOL) of patients with neurological symptoms.
Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener
... Show More
(5)
(4)
The research study and analysis of the integration of marketing communications and their impact on the marketing performance of a number of telecom companies, as included in the research problem to know the role of marketing communications community in achieving sales and market share, profitability and customer satisfaction. The importance of research begins to be the right choice for the elements of marketing communications, lead to savings in time, effort and money and create a more idea about the effectiveness of the application of the concept of integration. The research to determine the role of marketing communications in promoting the integration of the marketing performance of companies in the field of sales and marke
... Show More
(1)
Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
... Show More
(8)
(9)
(37)
(47)
(40)
Need organizations today to move towards strategic thinking which means analyzing situations faced by particular challenges of change in the external environment, which makes it imperative for The Organization That to reconsider their strategies and orientations and operations, a so-called re-engineering to meet those challenges and pressures, to try to achieve improvement root in the installation of the organization and methodscompletion of its work towards achieving high levels of performance and that is reflected to achieve its objectives, and this is what aims to Current search to deal with implications characteristics of strategic thinking in the stages of application re-engineering business of the company General Industries
... Show More
(1)
This article studies a comprehensive methods of edge detection and algorithms in digital images which is reflected a basic process in the field of image processing and analysis. The purpose of edge detection technique is discovering the borders that distinct diverse areas of an image, which donates to refining the understanding of the image contents and extracting structural information. The article starts by clarifying the idea of an edge and its importance in image analysis and studying the most noticeable edge detection methods utilized in this field, (e.g. Sobel, Prewitt, and Canny filters), besides other schemes based on distinguishing unexpected modifications in light intensity and color gradation. The research as well discuss
... Show More
The demand for electronic -passport photo ( frontal facial) images has grown rapidly. It now extends to Electronic Government (E-Gov) applications such as social benefits driver's license, e-passport, and e-visa . With the COVID 19 (coronavirus disease ), facial (formal) images are becoming more widely used and spreading quickly, and are being used to verify an individual's identity, but unfortunately that comes with insignificant details of constant background which leads to huge byte consumption that affects storage space and transmission, where the optimal solution that aims to curtail data size using compression techniques that based on exploiting image redundancy(s) efficiently.
Emotion could be expressed through unimodal social behaviour’s or bimodal or it could be expressed through multimodal. This survey describes the background of facial emotion recognition and surveys the emotion recognition using visual modality. Some publicly available datasets are covered for performance evaluation. A summary of some of the research efforts to classify emotion using visual modality for the last five years from 2013 to 2018 is given in a tabular form.