In this work, the relationship between the ionospheric parameters (Maximum Usable Frequency (MUF), Lowest Usable Frequency (LUF) and Optimum working Frequency (OWF)) has been studied for the ionosphere layer over the Iraqi zone. The capital Baghdad (44.42oE, 33.32oN) has been selected to represent the transmitter station and many other cities that spread over Iraqi region have represented as receiver stations. The REC533 communication model considered as one of the modern radio broadcasting version of ITU has been used to calculate the LUF parameter, while the MUF and OWF ionospheric parameters have been generated using ASAPS international communication model which represents one of the most advanced and accurate HF sky wave propagation models. The study has been conducted for the annual and seasonal time periods of the years (2009 and 2014) of the solar cycle 24. The results of the seasonal and annual tests have indicated that the interrelationship between the MUF and OWF with LUF was a fourth order polynomial equation, while the reciprocal relationship between the MUF and OWF was a simple relationship that could be represented by a linear regression equation. The reciprocal relationships between MUF, LUF and OWF parameters (present values) have shown a good fitting with the data generated using the international models (predicted values) and theoretical values calculated from the criterion equation.
In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.
... Show MoreAbstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.
The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine
... Show MoreThe ability of insurance companies to achieve goals depends on their ability to meet customers' requirements, and this requires them to identify target markets and respond to needs and wishes of the markets, the skill is to convince the company to operate what is in the interest of the customer if he is convinced the customer service provided to him, he would repeat to deal with, and where the cost of maintaining existing customers is less than the cost of attracting new customers, the insurance companies that is working hard to maintain their customers, the more customer satisfaction with the services provided has increased loyalty and weakened the ability of competitors lured.
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... Show MoreAbstract
For sparse system identification,recent suggested algorithms are
-norm Least Mean Square (
-LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named
-ZA-LMS,
تعد مرحلة الشباب من المرحلة المهمة التي يبدأ خلالها الاستقرار الانفعالي للفرد. ويعكس ماهو ايجابي في اساليب التربية التي تلقاها في مرحلتي الطفولة والمراهقة على سلوكه ومما نلاحظه ان هذه المرحلة فيها الكثير من المشكلات السلوكية لدى الشباب بصورة عامة وطلبة الجامعة بصورة خاصة، فهناك عوامل واسباب عامة اذا اجتمعت كلها او بعضها فقد تؤدي الى مشكلات وظواهر سلبية، ومن هذه العوامل اضطراب الشخصية ، والف
... Show MoreThe widespread use of the Internet of things (IoT) in different aspects of an individual’s life like banking, wireless intelligent devices and smartphones has led to new security and performance challenges under restricted resources. The Elliptic Curve Digital Signature Algorithm (ECDSA) is the most suitable choice for the environments due to the smaller size of the encryption key and changeable security related parameters. However, major performance metrics such as area, power, latency and throughput are still customisable and based on the design requirements of the device.
The present paper puts forward an enhancement for the throughput performance metric by p
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