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 data mining technology. Besides that, this paper implementation of 4 data mining classification techniques was experimented for extracting important insights from the tourism data set. The aims were to find out the best performing algorithm among the compared on the results to improve the business opportunities in the fields related to tourism. The results of the 4 classifiers correctly classifier the attributes were JRIP (84.09%), Random Tree (83.66%), J48 (85.50%), and REP Tree (82.47%). All the results will be analyzed and discussed in this paper.
This study investigated the prevalence of quinolones resistance proteins encoding genes (qnr genes) and co-resistance for fluoroquinolones and β-lactams among clinical isolates of Klebsiella pneumoniae. Out of 150 clinical samples, 50 isolates of K. pneumoniae were identified according to morphological and biochemical properties. These isolates were collected from different clinical samples, including 15 (30%) urine, 12 (24%) blood, 9 (18%) sputum, 9 (18%) wound, and 5 (10%) burn. The minimum inhibitory concentrations (MICs) assay revealed that 15 (30%) of isolates were resistant to ciprofloxacin (≥4µg/ml), 11 (22%) of isolates were resistant to levofloxacin (≥8 µg/ml), 21 (42%) of isolates were re
... Show MoreGround-based active optical sensors (GBAOS) have been successfully used in agriculture to predict crop yield potential (YP) early in the season and to improvise N rates for optimal crop yield. However, the models were found weak or inconsistent due to environmental variation especially rainfall. The objectives of the study were to evaluate if GBAOS could predict YP across multiple locations, soil types, cultivation systems, and rainfall differences. This study was carried from 2011 to 2013 on corn (Zea mays L.) in North Dakota, and in 2017 in potatoes in Maine. Six N rates were used on 50 sites in North Dakota and 12 N rates on two sites, one dryland and one irrigated, in Maine. Two active GBAOS used for this study were GreenSeeker and Holl
... Show MoreCorrelation equations for expressing the boiling temperature as direct function of liquid composition have been tested successfully and applied for predicting azeotropic behavior of multicomponent mixtures and the kind of azeotrope (minimum, maximum and saddle type) using modified correlation of Gibbs-Konovalov theorem. Also, the binary and ternary azeotropic point have been detected experimentally using graphical determination on the basis of experimental binary and ternary vapor-liquid equilibrium data.
In this study, isobaric vapor-liquid equilibrium for two ternary systems: “1-Propanol – Hexane – Benzene” and its binaries “1-Propanol –
... Show MoreBig data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a
... Show MoreIt has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlighting the diff
... Show MoreAn analytical approach based on field data was used to determine the strength capacity of large diameter bored type piles. Also the deformations and settlements were evaluated for both vertical and lateral loadings. The analytical predictions are compared to field data obtained from a proto-type test pile used at Tharthar –Tigris canal Bridge. They were found to be with acceptable agreement of 12% deviation.
Following ASTM standards D1143M-07e1,2010, a test schedule of five loading cycles were proposed for vertical loads and series of cyclic loads to simulate horizontal loading .The load test results and analytical data of 1.95
... Show MorePotential data interpretation is significant for subsurface structure characterization. The current study is an attempt to explore the magnetic low lying between Najaf and Diwaniyah Cities, In central Iraq. It aims to understand the subsurface structures that may result from this anomaly and submit a better subsurface structural image of the region. The study area is situated in the transition zone, known as the Abu Jir Fault Zone. This tectonic boundary is an inherited basement weak zone extending towards the NW-SE direction. Gravity and magnetic data processing and enhancement techniques; Total Horizontal Gradient, Tilt Angle, Fast Sigmoid Edge Detection, Improved Logistic, and Theta Map filters highlight source boundaries and the
... Show MoreWe examine 10 hypothetical patients suffering from some of the symptoms of COVID 19 (modified) using topological concepts on topological spaces created from equality and similarity interactions and our information system. This is determined by the degree of accuracy obtained by weighing the value of the lower and upper figures. In practice, this approach has become clearer.
The importance of the current study lies in the importance of the Tax policy that being considered one of the most important tools working on fulfilling the social, financial and economic goals and improving the investment environment in the country to become having the ability to activate the national economy. The current study has referred that ( Has the tax planning practiced by the Iraqi contribution companies led to increase the far-term tax outcome through getting benefit of the monetary funds and expansion in&nbs
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