درخت حوزه‌های تخصصی

Organizations nowadays focus on, not implementing ERP systems, but also leveraging ERP systems as part of their digital strategy. They holistically address people, processes, and technology for a digital transformation. Meanwhile, higher education institutions (HEIs) are also facing an imperative need for the implementation of modern technologies to stay competitive and differentiate them as an innovation leader. Higher education management is challenged with maintaining high-level information systems. These systems can generate complex real-time reports for effective resource allocation and better decision making. Enterprise Resource Planning (ERP) systems can help HEIs manage their resources and operations effectively. A study of ERP among 112 HEIs in Egypt was conducted. This study originally investigates the Egyptian HEIs’ perception of the ERP system as a new integrating tool for its value. The results showed that Egyptian HEIs are still at the embryonic level as the majority have not adopted these systems yet. However, ERP value has been undoubtedly perceived by HEIs’ managers. Therefore, the present study fruitfully reflected HEIs’ understanding of the imperative need of ERP systems as strategic systems for their competitiveness. Consequently, the study suggests that Egyptian HEIs and ERP vendors take steps to remove any barriers and accelerate the ERP adoption process. Also, this research contributes to the advancement of ERP concepts and characteristics from HEIs' standpoint and a grants practical verification to the higher education context. Overall, the study advances existing knowledge and research on ERP, strategic management systems, and HEIs.

The development of new technologies has confronted the entire domain of science and industry with issues of big data's scalability as well as its integration with the purpose of forecasting analytics in its life cycle. In predictive analytics, the forecast of near-future and recent past - or in other words, the now-casting - is the continuous study of real-time events and constantly updated where it considers eventuality. So, it is necessary to consider the highly data-driven technologies and to use new methods of analysis, like machine learning and visualization tools, with the ability of interaction and connection to different data resources with varieties of data regarding the type of big data aimed at reducing the risks of policy-making institution’s investment in the field of IT. The main scientific contribution of this article is presenting a new approach of policy-making for the now-casting of economic indicators in order to improve the performance of forecasting through the combination of deep nets and deep learning methods in the data and features representation. In this regard, a net under the title of P-V-L Deep: Predictive Variational Auto Encoders - Long Short-term Memory Deep Neural Network was designed in which the architecture of variational auto-encoder was used for unsupervised learning, data representation, and data reconstruction; moreover, long short-term memory was adopted in order to evaluate now-casting performance of deep nets in time-series of macro-econometric variations. Represented and reconstructed data in the generative network of variational auto-encoder to determine the performance of long-short-term memory in the forecasting of the economic indicators were compared to principal data of the net. The findings of the research argue that reconstructed data which are derived from variational auto-encoder embody shorter training time and outperform of prediction in long short-term memory compared to principal data.

Electrocardiogram (ECG) is a tool used for the electrical analysis of the status of human heart activity. When the ECG signal is recorded, it gets contaminated with different types of noises. So, for accurate analysis, noises must be eliminated from the ECG signal. There are different types of noises that contaminate the characteristics of ECG signal i.e Power line interference, baseline wander, Electromyogram (EMG). In this paper, different techniques have implemented for the removal of noises. A median filter is used for removal of DC component and Savitzky-Golay filter (SG) is used for smoothing noised waveform and then wavelet transform (db4) is used to decompose the ECG signal for removal of various artifacts. Wavelet transform provides the information in frequency and time domain and then thresholding has been applied for the implementation of algorithms in MATLAB. The measured results i.e. SNR(Signal to Noise ratio) and MSE(Mean square error) have been calculated using different databases like MIT-BIH, Long-term ST database, European ST-T database. The results are examined with proposed methods that are better than those reported in the literature.

This study aims at investigating the factors that affect a user’s satisfaction of accounting information systems based on the quality and the perceived usefulness of such systems, and the quality of data involved. The paper analyses the given factors on data collected from Bank Sumut,  Indonesia. In addition, this research also aims to find out whether the influence of perceived ease of use can be utilized as a moderating variable or not. the research is quantitative in terms of methodology and the sample pool consists of 112 people. The data used is primary data, which has been collected through the distribution of a questionnaire. Data has been analyzed through the Multiple Linear Regression and moderator test has been done using the Eviews 9 and SPSS software. The results contained in this study show that the variables can influence the accounting information system (AIS) user satisfaction significantly and that the information system quality plays an important role in the process. In addition, the quality of information systems, the information quality and perceived usefulness simultaneously affect the AIS of user satisfaction.

As mobile data traffic increases, and the number of services provided by the mobile network increases, service load flows as well, which requires changing in the principles, models, and strategies for media transmission streams serving to guarantee the given nature of giving a wide scope of services in Flexible and cost-effective. Right now, the fundamental question remains what number of network slices will be cost effective for slice managing and giving the required functionality. So, the aim is to improve the efficiency of mobile network by forming an ideal slice in a multi-service communication network. In this paper, we propose a model to demonstrate network resource allocation system that forms devoted network slices to serve particular types of services independently on shared infrastructure. This model solves the problem of creating a strategy to form multi-service core mobile communication network slices, which allow the providing of a wide scope of services with certain quality indicators according to the effective dynamic configuration of the system. A resource management system model is created, to provide a method that considers costs related with excessive resource allocation, and also reduces the number of network recalculations, allowing for a reasonable proportion of management costs and Qualities of Service.