Tourism plays an important role in Malaysia’s economic development as it can boost business opportunity in its surrounding economic. By apply data mining on tourism data for predicting the area of business opportunity is a good choice. Data mining is the process that takes data as input and produces outputs knowledge. Due to the population of travelling in Asia country has increased in these few years. Many entrepreneurs start their owns business but there are some problems such as wrongly invest in the business fields and bad services quality which affected their business income. The objective of this paper is to use data mining technology to meet the business needs and customer needs of tourism enterprises and find the most effective

Abstract

               Documentary credits are considered successful means to reduce imports, especially unnecessary imports that lead to the outflow of foreign currency from the country. However, due to the backwardness of the banking methods, the reintroduction of documentary credits after 2003 did not effectively contribute to reducing import rates. This has had a negative impact on the Iraqi economy and made it vulnerable to external markets. Documentary credits are also considered the best way to ensure payment in international trade, providing independent credit support and sufficient security for exporters and importers against commerci

Because of the fierce competition between service organizations on the one hand and the increasing demands of customers on the other. Therefore, these organizations sought to distinguish their service by taking care of all aspects. One of these important aspects is the service encounter environment and its reflection on customer emotions, so we choose the current research to clarify the importance and impact on customer satisfaction, the problem of research is how the interest of Iraqi restaurants in the service encounter environment and how to care about its elements and whether this interest is sufficient to reflect the satisfaction of the customer. the goal of the current research was to clarify how much the application of the

Background: Fractures of the humeral shaft
accounting for approximately 3% of all
fractures. There is a wide array of good
options for their treatment and controversy
over the best methods. Although good
techniques of osteosynthesis are available, the
aim of this article is toemphasize on the benefit
and good outcome of conservative treatment
for properly selected cases to decrease the cost
and avoid the complications of surgery.

The corrosion behavior of copper and carbon steel in 1M concentration of hydrochloric acid (HCl) and sulphuric acid (H2SO4) has been studied. The corrosion inhibition of copper and carbon steel in 1M concentration of hydrochloric acid (HCl) and sulphuric acid (H2SO4) by Ciprofloxacin has been investigated. Specimens were exposed in the acidic media for 7 hours and corrosion rates evaluated by using the weight loss method. The effect of temperature (from 283 ºK to 333 ºK), pH (from 1to 6), inhibitor concentration (10-4 to 10-2) has been studied. It was observed that sulphuric acid environment was most corrosive to the metals because of its oxidizing nature, followed by hydrochloric acid. The rate of metal dissolution increased with incre

The aim of this project was to study the in vitro effect of antineoplastic drugs (vincristine and vinblastine) on mice spermatozoa. Eighteen adult (age 8-9 weeks) male mice were divided into three groups equally. The animals in each group were slain by cervical dislocation, the testes were removed and two tails of epididymides isolated. Spermatozoa were obtained from the two tails of epididymides by mincing in 500 µl TCM-199.The first group non-treated (unadded) as a control group, second group added 10 µg/ml of vincristine to TCM-199 and the third group added 10 µg/ml of vinblastine to TCM-199. After 10 minutes from added of vincristine and vinblastin measured the following test: spermatozoa activity, percentage dead spermatozoa and mor

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c