<p><span>The importance and benefits of healthcare mobile applications is increasing rapidly, especially when such applications are connected to the internet of things (IoT). This paper d<a name="_Hlk39949144"></a>escribes a smart knowledge-based system (KBS) that helps patients showing symptoms of Influenza verify being infected with Coronavirus, commonly known as COVID-19. In addition to the systems’ diagnostic functionality, it helps these patients get medical assistance fast by notifying medical authorities using the IoT. This system displays patient’s location, phone number, date and time of examination. During the applications’ development, the developers used Twilio, short message service (SMS), WhatsApp, and Google map applications.</span></p>

In this paper, we introduce and study preprocessing signal for speech emotion recognition. The aim of our work is to get pure signal which is created by sampling the signal from speaker. The discrimination between speech and music waves was achieved. A good signal is obtained by using preprocessing then it used for feature extraction. The files we used in this paper are wave-type for male, female and music have sample rate 48000, bit resolution is 16-bits and Mono channel. The Berlin dataset and RAVDESS dataset are used in this work.

For making the most favorable financial decisions possible, it is essential to have an understanding of aspects and the factors which can play a role in the decision-making. In contrast to previous research on the subject, which has only examined a single factor in making investment decisions, our study takes a more holistic approach by looking at several factors. The purpose of this study was to discover the elements that influence investment decisions made by financial organizations that are listed on Iraqi stock exchanges (ISX). The research was carried out on the six companies that made up the study’s sample size. For the purpose of data collection, the researcher utilized a structured questionnaire that was delivered to the respondents in an individual capacity. The questionnaire contained eight items. The factors of the questionnaire were analyzed with respect to normal distribution, the problem of linear multiplicity, the validity of the questionnaire in terms of content and appearance, the stability of the questionnaire by the split-half method, and the test and re-test method. In addition, the research hypotheses were tested on both the independent variables and the dependent variables. We calculated the mean, standard deviation, weight percentile, and coefficient of variance from the collected data. The significance of the connection between the dimensions of the decision-making factors was clarified through the use of Spearman’s correlation coefficient and the t test. We concluded that in the last step of the proposed model there is an increase in coefficients of determination and it reaches a value of (0.98), which is a very excellent and almost complete interpretation of the impact of dimensions extracted in the model and their impact on investment decision. As is noted, a slight decline in the value of the regression coefficient for all variables occurred, and also we noticed that the signs for the coefficients for the five variables are positive, meaning that they reflect the extent of the direct effect of those variables in making the investment decision. The response rate for the questionnaire was 97.7%.

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