The Dirichlet process is an important fundamental object in nonparametric Bayesian modelling, applied to a wide range of problems in machine learning, statistics, and bioinformatics, among other fields. This flexible stochastic process models rich data structures with unknown or evolving number of clusters. It is a valuable tool for encoding the true complexity of real-world data in computer models. Our results show that the Dirichlet process improves, both in distribution density and in signal-to-noise ratio, with larger sample size; achieves slow decay rate to its base distribution; has improved convergence and stability; and thrives with a Gaussian base distribution, which is much better than the Gamma distribution. The performance depends greatly on the choice of base distribution. The higher the value of α (a concentration parameter), the better the clustering and noise suppression. The distributional behavior of data can be approximated rigorously by the biorthogonal wavelet analysis. Since the Dirichlet process is an interesting object of observation, we computed it for a few wavelet bases and among them, we found that the Cohen-Daubechies-Feauveau (CDF) basis is the one that captures the Dirichlet process most accurately. Our results may be useful in applying the Dirichlet process to real-world experimental data and in developing Bayesian non-parametric methods.
This paper investigates a new approach to the rapid control of an upper limb exoskeleton actuator. We used a mathematical model and motion measurements of a human arm to estimate joint torque as a means to control the exoskeleton’s actuator. The proposed arm model is based on a two-pendulum configuration and is used to obtain instantaneous joint torques which are then passed into control law to regulate the actuator torque. Nine subjects volunteered to take part in the experimental protocol, in which inertial measurement units (IMUs) and a digital goniometer were used to measure and estimate the torque profiles. To validate the control law, a Simscape model was developed to simulate the arm model and control law in which measurem
... Show MoreThis research investigated the importance and priorities of the project overhead costs in Iraq via a questionnaire using the fuzzy analytic hierarchy process technique (FAHP). Using this technique is very important in the uncertain circumstances as in our country. The researcher reached to frame an equation through the results of the priorities of weights include the percentages of each of the main items of the project overhead costs. The researcher tested this equation by applying it to one of the completed projects and the results showed suitability for the application. The percentages of the (salaries, grants, and incentives) and (fieldwork requirements) in equation represent approximately two-thirds of project overhe
... Show MoreIn the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used
... Show MoreFree Space Optics (FSO) plays a vital role in modern wireless communications due to its advantages over fiber optics and RF techniques where a transmission of huge bandwidth and access to remote places become possible. The specific aim of this research is to analyze the Bit-Error Rate (BER) for FSO communication system when the signal is sent the over medium of turbulence channel, where the fading channel is described by the Gamma-Gamma model. The signal quality is improved by using Optical Space-Time Block- Code (OSTBC) and then the BER will be reduced. Optical 2×2 Alamouti scheme required 14 dB bit energy to noise ratio (Eb/N0) at 10-5 bit error rate (BER) which gives 3.5 dB gain as compared to no diversity scheme. Th
... Show MoreThis study investigates the effects of Al-Doura oil refinery effluent, in Baghdad city, on the water quality of the Tigris River using the Canadian Water Quality Index (CCME WQI) and Rivers Maintaining System (1967). Water samples were collected monthly from Tigris River at three stations, which are Al-Muthanna Bridge (upstream), Al-Doura Refinery (point source), and Al–Zafaraniya city (downstream) from October 2020 to April 2021. Fourteen water quality parameters were studied, namely pH (6.50-8.10), Water Temperature (WT) (5.00-27.00 °C), Electrical Conductivity (EC) (877.00-1192.00 μs/cm), Dissolved Oxygen (DO) (5.03-7.57 mg/L), Biological Oxygen demand (BOD) (0.53-2.23 mg/L), Total Dissolved S
The investor needs to a clear strategy for the purpose of access to the financial market, that is, has a plan to increase The share of the profits thinking entrepreneur and new, and highlights the importance of this in that it sets for the investor when it goes to the market, and when it comes out of it, and at what price to buy or sell the stock, and what is the the amount of money it starts. Fortunately, he does not need to invent his own investment strategy, because over the years the development of effective methods of buying and selling, and once you understand how to work these methods investor can choose the most appropriate methods and adapted image that fit his style investment .
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... Show MoreStatistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c
... Show MoreGlobalisation and rapid environmental change have created many challenges for public and private organisations across Iraq as a developing country, particularly in the higher education sector. This includes, for example, decreases in government funding; increased demand for higher education; a need for economic transformation, and related competitiveness of organizations. Such challenges require exceptional leaders and strategic planning in order to take action to improve. In Iraq, the higher education sector is still one of the main foundations in progressing the knowledge economy. Studies into leadership style, strategic planning processes, and the importance of leadership and organisational culture to an organisation’s success have bee
... Show MoreThe trading banks in Iraq invest their funds according to regulations imposed by the Central Bank in Iraq in different financial fields like stock exchanges, acquire stocks as assets that could be sold at any time as well as make loans and contributing in corporations establishment also magnitude foreign capital through direct contacts with foreign exchange markets.
We can summarize the problem of this paper as shortage in mathematical models that used in studying and analyzing these investments and according to this problem we used (a constructed mathematical model ) consists of three major indicators: profitability of total investment assets which is divided into three sub-indicators: owners equity risk indicator, debits risk i
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