<span>The Dijkstra algorithm, also termed the shortest-route algorithm, is a model that is categorized within the search algorithms. Its purpose is to discover the shortest-route, from the beginning node (origin node) to any node on the tracks, and is applied to both directional and undirected graphs. However, all edges must have non-negative values. The problem of organizing inter-city flights is one of the most important challenges facing airplanes and how to transport passengers and commercial goods between large cities in less time and at a lower cost. In this paper, the authors implement the Dijkstra algorithm to solve this complex problem and also to update it to see the shortest-route from the origin node (city) to the destination node (other cities) in less time and cost for flights using simulation environment. Such as, when graph nodes describe cities and edge route costs represent driving distances between cities that are linked with the direct road. The experimental results show the ability of the simulation to locate the most cost-effective route in the shortest possible time (seconds), as the test achieved 95% to find the suitable route for flights in the shortest possible time and whatever the number of cities on the tracks application.</span>
IT systems and data that you store, and process are valuable resources that need protection. Validation and reliability of information are essential in networks and computer systems. The communicating is done by two parties via an unsafe channel require a way to validate the data spent by one party as valid (or unaltered) by the other party. In our study, we suggest new one-way defragmentation algorithm to implement message authentication and integration in program execution. These software applications are readily available and freely available because most of the hash functions are faster than their existing radioactive blocks.
The investment and progress made in the transfer of technology by the Gulf cooperation council (GCC) countries to industrialize their countries are briefly reviewed. About 31.42 billion US$ was spent between, and 2005 to 2015 establish over 3280 industrial operating plants. Manufacturing industry and other sectors contribution to national income has increased significantly. However, serious difficulties and obstacles still face the GCC industry, and these are specified and reported. The status and level of expenditure of R & D were low, and the present R & D system is deficient. These might have been partly responsible for the above industrial problems. Arab countries spent 0.76 % of their GNP on R & D in 1989 compared to 2.92 % of GNP by developed countries. The expenditure on R & D is increased by 10 % for the same period. Examples of indigenous R & D showed success in achieving innovative technologies because the environment for R & D was right. Some corrective measures to present R & D systems are recommended.
The effects of climate change, such as droughts, storms, and extreme weather, are increasingly being felt around the world. Greenhouse gases are the primary contributors to climate change, with carbon dioxide (CO2) being the most significant. In fact, CO2 accounts for a significant percentage of all greenhouse gas emissions. As a result, reducing CO2 emissions has become a critical priority for mitigating the impacts of climate change and preserving our planet for future generations. Based on simulation and data mining technologies that use historical data, CO2 is expected to continue to rise. Around the world, 80% of CO2 emissions come from burning fossil fuels, mostly in the automotive or manufacturing industries. Governments have created policies to control CO2 emissions by focusing them on either consumers or manufacturers, in both developed and developing nations. Within the scope of this project, an investigation of vehicle emissions will be carried out using various attributes included within the vehicle dataset, as well as the use of many data mining techniques via the utilization of an orange application. The practical program is an example of organization, and the example will be about cars, exploring data, and figuring out how much gas will be needed. CO2 is taken away from cars, and we will use the CARS.csv file, which has data for a group of car types. It has a table with 36 records that shows the model, weight, and amount of carbon dioxide based on the car's size and weight.
<p><span lang="EN-US">Today, the world lives in the era of information and data. Therefore, it has become vital to collect and keep them in a database to perform a set of processes and obtain essential details. The null value problem will appear through these processes, which significantly influences the behaviour of processes such as analysis and prediction and gives inaccurate outcomes. In this concern, the authors decide to utilise the random forest technique by modifying it to calculate the null values from datasets got from the University of California Irvine (UCL) machine learning repository. The database of this scenario consists of connectionist bench, phishing websites, breast cancer, ionosphere, and COVID-19. The modified random forest algorithm is based on three matters and three number of null values. The samples chosen are founded on the proposed less redundancy bootstrap. Each tree has distinctive features depending on hybrid features selection. The final effect is considered based on ranked voting for classification. This scenario found that the modified random forest algorithm executed more suitable accuracy results than the traditional algorithm as it relied on four parameters and got sufficient accuracy in imputing the null value, which is grown by 9.5%, 6.5%, and 5.25% of one, two and three null values in the same row of datasets, respectively.</span></p>
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