The importance of this research lies in shedding light on the concept of techno-strategy for information management from vital and important topics that showed response for change in all areas of life. As this necessitates the updating and changing of it in order to achieve its strategic goals and enhance its technological advantage. The research problem looked at the role of the information technology system (ITS) in enhancing risk management in general directorates for sports and school activity from the viewpoint of its department heads. The research aimed at the relationship of information techno-strategy in risk management and the ratios of the contribution of information techno-strategy in risk management from the viewpoint of heads o

The aim of the current research is to explore the health, psychological, and social implications of Internet addiction. Internet addiction is a new type of addiction, which negatively affects an individual’s life and creates social problems, psychological and nervous disorders. The research is divided into three sections: The first section is devoted to the definition of the research and includes the research problem, its importance in addition to the objectives, and the search terms were defined in it. The second section included the concept of addiction on the Internet and the causes, symptoms of addiction, forms, and previous studies were reviewed. As for the third topic, it deals with the theories explaining Internet addiction and

This paper presents designing an adaptive state feedback controller (ASFC) for a magnetic levitation system (MLS), which is an unstable system and has high nonlinearity and represents a challenging control problem. First, a nonadaptive state feedback controller (SFC) is designed by linearization about a selected equilibrium point and designing a SFC by pole-placement method to achieve maximum overshoot of 1.5% and settling time of 1s (5% criterion). When the operating point changes, the designed controller can no longer achieve the design specifications, since it is designed based on a linearization about a different operating point. This gives rise to utilizing the adaptive control scheme to parameterize the state feedback controll

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

This paper deals with the thirteenth order differential equations linear and nonlinear in boundary value problems by using the Modified Adomian Decomposition Method (MADM), the analytical results of the equations have been obtained in terms of convergent series with easily computable components. Two numerical examples results show that this method is a promising and powerful tool for solving this problems.

<span lang="EN-GB">This paper highlights the barriers that have led to a delay in the implementation of E-Health services in Iraq. A new framework is proposed to improve the E-Health sector using a SECI model which describes how explicit and tacit knowledge is generated, transferred, and recreated in organizations through main stages (socialization, externalization, combination and internalization). Class association rules (CARs) is integrated to mine the SECI model by extracting related rules which correspond to the medical advice. The proposed framework (SECICAR) can be done through a web portal to assemble healthcare professionals, patients in one environment. SECICAR will be applied to the hypertension community to show th

Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica