Microfinance Institutions (MFIs) offers small loans with easy repayment system and till now these institutions have served millions of needy people around the globe. This study highlights the hurdles influence the smooth working and growth of Microfinance institution in Egypt. The structured interviews were conducted from the top and mid-level managers of MFI's. This study revealed that interest rate, political and economic conditions, corruption, customer outreach, competition and technology are the important elements for MFI's success. It is evident that lack of use of technology and less importance drawn on customer outreach programs are the main challenges of MFI's in Egypt. This study provides a roadmap for practitioners and strategic

The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. This work modernize the feedforward neural network, so the secret message will be encrypted by unsupervised neural network method to get the cipher text that can be decrypted using the same network to get the original text. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding lengths. In this work, the key is the final weights

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

This research studies Reinforcing and applied load of  Wear Rate for Epoxy composites contains from epoxy resin (Ep) as a matrix material and reinforced by Gawain red wood flour , Russian white wood flour , glass powder and rock wool fibers , with volume fraction (20%) for all samples in lab conditions.  by using the load (10,20 ,30 ,40) Newton of iron disc for testing  time(10) minute, and the results have shown that the reinforcing of epoxy resin led to decrease  wear rate for all samples except the hybrid composites reinforced earth glass powder , that the wear rate values  decrease  from   (22×10-9g/cm) to (4×10-9g/cm) of composite material(Ep+R.W.F) and thus(Ep+W.W.F)   at la

The emergence of oil fields and subsequent changes in adjacent land use are known to affect settlements and communities. Everywhere the industry emerges, there is little understanding about the impact of oil fields on land use in the surrounding areas. The oil industry in Iraq is one of the most important industries and is almost the main industry in the Iraqi economic sector, and it is very clear that this industry is spread over large areas, and at the same time adjoins with population communities linked to it developmentally.

The rapid development and expansion of oil extraction activities in various regions has led to many challenges related to land-use planning and management. Here, the problem of research  arises on th

Radiological assessment for the East Baghdad oilfield-southern part was conducted in the current study. 10 samples (scale, soil, sludge, water, and oil) from the different stages of oil production were collected. 232Th, 226Ra, and 40K in the samples were analyzed with 40% efficiency for Gamma spectrometry. system based on HPGe. The findings indicated that the examined sites exhibit comparatively lower levels of NORM contamination, in contrast to other global oilfields. Nevertheless, certain areas, particularly those within separation stages, demonstrate relatively elevated NORM concentrations exceeding the global average in soil and sludge. The maximum value of 226Ra, 232Th, was found in sludge sample the findings indicated that ove

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

As the reservoir conditions are in continuous changing during its life, well production rateand its performance will change and it needs to re-model according to the current situationsand to keep the production rate as high as possible.Well productivity is affected by changing in reservoir pressure, water cut, tubing size andwellhead pressure. For electrical submersible pump (ESP), it will also affected by numberof stages and operating frequency.In general, the production rate increases when reservoir pressure increases and/or water cutdecreases. Also the flow rate increase when tubing size increases and/or wellhead pressuredecreases. For ESP well, production rate increases when number of stages is increasedand/or pump frequency is