Portable devices such as smartphones, tablet PCs, and PDAs are a useful combination of hardware and software turned toward the mobile workers. While they present the ability to review documents, communicate via electronic mail, appointments management, meetings, etc. They usually lack a variety of essential security features. To address the security concerns of sensitive data, many individuals and organizations, knowing the associated threats mitigate them through improving authentication of users, encryption of content, protection from malware, firewalls, intrusion prevention, etc. However, no standards have been developed yet to determine whether such mobile data management systems adequately provide the fundamental security functions demanded by organizations and whether these functions have been securely developed. Therefore, this paper proposes a security framework for mobile data that combines core security mechanisms to avoid these problems and protects sensitive information without spending time and money deploying several new applications.
The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s
... Show MoreMeasuring university teachers attitudes towards the security man Summary This research aims to study the measurement of university teachers attitudes towards the security man, and represented the research sample (196) of teachers, including 124 males and 72 females from different faculties of Salah al-Din - Erbil University. The researchers adopted on a scale (Al-Tarawneh 2008), as amended, and its development, the scale consists of four areas and (28) paragraph covers paragraphs measure the beliefs and feelings of the individual towards the security man as the theme of direction. The research sample answered all the paragraphs of the scale grade five similar styles (Likert) (strongly OK, OK, neutral, non-OK, Strongly Disagree). The rese
... Show MoreDifferent ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach
The international system that established the United Nations after the end of the Second World War witnessed many changes. These changes overshadowed the nature of the work of the international organization, especially its first and most important executive organ (the Security Council). This has sometimes weakened and dulled the Security Council's role in performing the tasks stipulated in the Charter of the Organization, which has led the Organization itself to work on reforms within it in general and to seek reforms in the Security Council in particular. Academic and advisory efforts were made to submit proposals for amendment to be reflected on the Council's performance effectiveness.
Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an
... Show More<p><span>This research deals with the feasibility of a mobile robot to navigate and discover its location at unknown environments, and then constructing maps of these navigated environments for future usage. In this work, we proposed a modified Extended Kalman Filter- Simultaneous Localization and Mapping (EKF-SLAM) technique which was implemented for different unknown environments containing a different number of landmarks. Then, the detectable landmarks will play an important role in controlling the overall navigation process and EKF-SLAM technique’s performance. MATLAB simulation results of the EKF-SLAM technique come with better performance as compared with an odometry approach performance in terms of measuring the
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