The aimed of the research was recognize the Big five personality factors and Academic procrastination among Baghdad university students, recognized differences between the gender according to   Big five personality factors and Academic procrastination , to recognized differences between specialization (scientific, human), and to recognize the relationship Between the variables of the research, and the extend of contribution Big five personality factors in Academic procrastination , to achieve these aims , Adopt scale to measure the Big five personality factors for (John Danahue & Kentle) , As we as the preparation of scale Based on An amber of previous scales to measure Academic procrastination, After processing the data st

The aesthetic contents of data visualization is one of the contemporary areas through which data scientists and designers have been able to link data to humans, and even after reaching successful attempts to model data visualization, it wasn't clear how that reveals how it contributed to choosing the aesthetic content as an input to humanize these models, so the goal of the current research is to use The analytical descriptive approach aims to identify the aesthetic contents in data visualization, which the researchers interpreted through pragmatic philosophy and Kantian philosophy, and analyze a sample of data visualization models to reveal the aesthetic entrances in them to explain how to humanize them. The two researchers reached seve

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

The development of information systems in recent years has contributed to various methods of gathering information to evaluate IS performance. The most common approach used to collect information is called the survey system. This method, however, suffers one major drawback. The decision makers consume considerable time to transform data from survey sheets to analytical programs. As such, this paper proposes a method called ‘survey algorithm based on R programming language’ or SABR, for data transformation from the survey sheets inside R environments by treating the arrangement of data as a relational format. R and Relational data format provide excellent opportunity to manage and analyse the accumulated data. Moreover, a survey syste

Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati

COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduce