Learning is the process of gaining knowledge and implementing this knowledge on behavior. The concept of learning is not strict to just human being, it expanded to include machine also. Now the machines can behave based on the gained knowledge learned from the environment. The learning process is evolving in both human and machine, to keep up with the technology in the world, the human learning evolved into micro-learning and the machine learning evolved to deep learning. In this paper, the evolution of learning is discussed as a formal survey accomplished with the foundation of machine learning and its evolved version of learning which is deep learning and micro-learning as a new learning technology can be imple

Il semble que Khattabi était un linguiste, avec un endroit linguistique pour comprendre les textes de conversations et des mots étranges en particulier. Langue, et chacun avait ses arguments et ses preuves. Ses corrections incluaient la mélodie dans les mouvements, telle qu'une dilution plus serrée, la dilution de l'agitateur, le remplacement d'un autre mouvement, ou une autre rotation des mouvements, et le changement de structure morphologique du mot qui en résultait, ainsi que l'alerte sur les conséquences des lettres, Certaines de ces erreurs sont dues à la langue, et certaines sont considérées comme un type de déformation ou de fausse représentation connue de certains spécialistes, ce qui constitue un précédent louable

The research is an attempt to investigate experimentally the influence of teacher’s errors correction and students’ errors correction on teaching English at the College of Physical Education for Women. Errors are seen as a natural way for developing any language but teachers are puzzled the way they can correct these errors. So, this research gives some idea of using two types of errors correction. The sample of the research is female students of the first year stage at the College of Physical Education for Women of the academic year 2009-2010. The whole population of the research is (94) students while the sample is (64). Thus, the sample represents 68% from the population of the research. The sample represents It is hypothesized th

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

This article explores the process of VGI collection by assessing the relative usability and accuracy of a range of different methods (Smartphone GPS, Tablet, and analogue maps) for data collection amongst different demographic and educational groups, and in different geographical contexts. Assessments are made of positional accuracy, completeness, and data collectors’ experiences with reference to the official cadastral data and the administration system in a case-study region of Iraq. Ownership data was validated by crowd agreement. The result shows that successful VGI projects have access to varying data collection methods.

Due to the easily access to the satellite images, Google Earth (GE) images have become more popular than other online virtual globes. However, the popularity of GE is not an indication of its accuracy. A considerable amount of literature has been published on evaluating the positional accuracy of GE data; however there are few studies which have investigated the subject of improving the GE accuracy. In this paper, a practical method for enhancing the horizontal positional accuracy of GE is suggested by establishing ten reference points, in University of Baghdad main campus, using different Global Navigation Satellite System (GNSS) observation techniques: Rapid Static, Post-Processing Kinematic, and Network. Then, the GE image for the study

In this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the

      This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.