Development and evaluation of an instructional LiveBinders for learning selected computer studies concept in Ilorin Metropolis

This research was developed and evaluated an instructional LiveBinders for learning selected computer Studies concepts in Ilorin Metropolis, Nigeria. In this research, the design and development model was used. The participants in the study were five computer studies teachers, five computer science experts, and five educational technology experts were chosen at random. The following research instruments were used in this study: a developed computer storage device for computer studies, an expert rating guide of educational technology, and a subject content validation questionnaire. Research questions were answered using percentages and mean. The study concluded that if LiveBinders are properly integrated into learning, computer studies learning can be improved. As a result, it was suggested that students be encouraged to use LiveBinders for learning regardless of a subject area.

Iterative Methods for the Computation of the Perron Vector of Adjacency Matrices

The power method is commonly applied to compute the Perron vector of large adjacency matrices. Blondel et al. [SIAM Rev. 46, 2004] investigated its performance when the adjacency matrix has multiple eigenvalues of the same magnitude. It is well known that the Lanczos method typically requires fewer iterations than the power method to determine eigenvectors with the desired accuracy. However, the Lanczos method demands more computer storage, which may make it impractical to apply to very large problems. The present paper adapts the analysis by Blondel et al. to the Lanczos and restarted Lanczos methods. The restarted methods are found to yield fast convergence and to require less computer storage than the Lanczos method. Computed examples illustrate the theory presented. Applications of the Arnoldi method are also discussed.

Hiragana Handwriting Recognition Using Deep Neural Network Search

<span id="orcid-id" class="orcid-id-https">These days there is a huge demand in “storing the information available in paper documents into a computer storage disk”. Digitizing manual filled forms lead to handwriting recognition, a process of translating handwriting into machine editable text. The main objective of this research is to to create an Android application able to recognize and predict the output of handwritten characters by training a neural network model. This research will implement deep neural network in recognizing handwritten text recognition especially to recognize digits, Latin / Alphabet and Hiragana, capture an image or choose the image from gallery to scan the handwritten text from the image, use the live camera to detect the handwritten text real – time without capturing an image and could copy the results of the output from the off-line recognition and share it to other platforms such as notes, Email, and social media. </span>

Assignment Algorithm of Computer Storage Management Partition and Its Implementation

This paper is about the algorithm of computer storage management partition and its implementation. First, we introduced the background and significance of the project, as well as the principle of technology used by the author in this project. This includes the principles of storage management, partition allocation technology and recycling technology. Then, a detailed analysis of the operating system primary storage allocation of a simple algorithm and one of its implementation., which mainly is to achieve a variable partition of the storage management allocation and recycling technology. Variable partition management usually uses a variety of methods, and our design are the first adaptive algorithm and the use of the best adaptive algorithm. Then it is followed by the test results of the system and discussion of its advantages and disadvantages. The entire storage management partition allocation algorithm and its implementation is entirely in accordance with the primary storage management of the operating system and effective use, in order to achieve a certain level of economic and technical value.

Fragmentation of Thinking Structure’s Students to Solving the Problem of Application Definite Integral in Area

This study aims to reveal the fragmentation of thinking structure’s students in solving the problems of application definite integral in area. Fragmentation is a term on the computer (storage) that is highly relevant correlated with theoretical constructions that occur in the human brain (memory). Almost every student has a different way to construct a problem. That’s very interesting to finding a process of thinking students. Researcher works in three cases. The findings of this study were two in every case, which the fragmentation whole construction and fragmentation construction pseudo. Data this study a full description and in-depth exploration of the students majoring in mathematics education since high school that has been learned about the material Integral course and the area.