• International Journal of Computer Science & Network Security
• /
• v.22 no.6
• /
• pp.230-240
• /
• 2022

Sharing of online videos via internet is an emerging and important concept in different types of applications like surveillance and video mobile search in different web related applications. So there is need to manage personalized web video retrieval system necessary to explore relevant videos and it helps to peoples who are searching for efficient video relates to specific big data content. To evaluate this process, attributes/features with reduction of dimensionality are computed from videos to explore discriminative aspects of scene in video based on shape, histogram, and texture, annotation of object, co-ordination, color and contour data. Dimensionality reduction is mainly depends on extraction of feature and selection of feature in multi labeled data retrieval from multimedia related data. Many of the researchers are implemented different techniques/approaches to reduce dimensionality based on visual features of video data. But all the techniques have disadvantages and advantages in reduction of dimensionality with advanced features in video retrieval. In this research, we present a Novel Intent based Dimension Reduction Semi-Supervised Learning Approach (NIDRSLA) that examine the reduction of dimensionality with explore exact and fast video retrieval based on different visual features. For dimensionality reduction, NIDRSLA learns the matrix of projection by increasing the dependence between enlarged data and projected space features. Proposed approach also addressed the aforementioned issue (i.e. Segmentation of video with frame selection using low level features and high level features) with efficient object annotation for video representation. Experiments performed on synthetic data set, it demonstrate the efficiency of proposed approach with traditional state-of-the-art video retrieval methodologies.

• Journal of the Korean School Mathematics Society
• /
• v.25 no.4
• /
• pp.307-332
• /
• 2022

This action research was carried out to help students learn fractions computation by making and using semi-concrete fraction manipulatives that can be used continuously in math classes. For this purpose, the researcher and students made semi-concrete fraction manipulatives and learned how to use these through reviewing the previously learned fraction contents over 4 class sessions. Afterward, through the 14 classes (7 classes for learning to reduce fractions and to a common denominator, 7 classes for adding and subtracting fractions with different denominators) in which the principle inquiry learning model was applied, students actively engaged in learning activities with fraction manipulatives and explored the principles underneath the manipulations of fraction manipulatives. Students could represent various fractions using fraction manipulatives and solve fraction computation problems using them. The achievement evaluation after class found that the students could connect the semi-concrete fraction manipulatives with fraction representation and symbolic formulas. Moreover, the students showed interest and confidence in mathematics through the classes using fraction manipulatives.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.34 no.1
• /
• pp.31-40
• /
• 2024

Recently, static analysis-based signature and pattern detection technologies have limitations due to the advanced IT technologies. Moreover, It is a compatibility problem of multiple architectures and an inherent problem of signature and pattern detection. Malicious codes use obfuscation and packing techniques to hide their identity, and they also avoid existing static analysis-based signature and pattern detection techniques such as code rearrangement, register modification, and branching statement addition. In this paper, We propose an LLVM IR image-based automated static analysis of malicious code technology using machine learning to solve the problems mentioned above. Whether binary is obfuscated or packed, it's decompiled into LLVM IR, which is an intermediate representation dedicated to static analysis and optimization. "Therefore, the LLVM IR code is converted into an image before being fed to the CNN-based transfer learning algorithm ResNet50v2 supported by Keras". As a result, we present a model for image-based detection of malicious code.

• Journal of Educational Research in Mathematics
• /
• v.26 no.1
• /
• pp.143-157
• /
• 2016

This study aims to find out the feasibility and effectiveness of mathematical games as a way to provide primary pre-service teachers with doing mathematics. The game had induced the active participation of elementary pre-service teachers. Through transforming the game, the teachers have been able to experience of mathematical problem posing and generating mathematical representation. Based on this, we discuss the role of mathematical games as a method of pre-service teacher education.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2000.04b
• /
• pp.421-428
• /
• 2000

The preliminary stage of structural design is very crucial step whose results have great effects on the structural performance, construction, economy, and aesthetics through the following design stages. However, it is extremely difficult to computerize the information and knowledge used in the preliminary design stage because it lacks of formality of representation of designers' experience and intuition. To address such issue the concept of an artificial neural network has been adopted to develop preliminary design system for cable-stayed bridges in this paper. The artificial neural network has been proved that it has the ability of learning design experience and providing a good design alternative.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.7
• /
• pp.159-169
• /
• 1994

In this paper, we develop a prototype of ITS(Intelligent Tutoring Systems) system: UNIX TUTOR. It is designed for the purpose of teaching the UNIX beginners the principal concepts of UNIX and the shell commands using the communication between the student and the system. UNIX TUTOR engages the student in a two-way conversation that is mixed-initiative dialogue and attempts to teach the student UNIX via the Socratic method of guided discovery and the Coaching method interchangeably. And the student model is based on both the overlay model and the buggy model together. Thus TUTOR aims at teaching the students effectively whose levels of learning are different using various explanations which are determined by the student model. Because the knowledge representation for UNIX-TUTOR is based on the frame structure and the production rules it is easy to represent the complicated constructs. UNIX TUTOR is implemented on the SPARC station using X/Motif and C for cp command among 10 ones which were selected.

• Research in Mathematical Education
• /
• v.18 no.4
• /
• pp.289-305
• /
• 2014

The current mathematical education calls for a learning environment from the constructionism perspective that actively creates mathematical objects. This research first analyzes JavaMAL's expression 'move' that enables students to express the agent's behavior constructively before they learn vector as a formal concept. Since expression 'move' is based on a coordinate, it naturally corresponds with the expression of vectors used in school mathematics and lets students take an embodied approach to the concept of vector. Furthermore, as a design tool, expression 'move' can be used in various activities that include vector structure. This research studies the educational significance entailed in JavaMAL's expression 'move'.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.55 no.3
• /
• pp.117-122
• /
• 2006

The paper is proposed artificial neural network(ANN) sensorless control of induction motor drive with fuzzy learning control-fuzzy neural network(FLC-FNN) controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also this paper is proposed. speed control of induction motor using FLC-FNN and estimation of speed using ANN controller. The back Propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed so that the actual state variable will coincide with the desired one. The proposed control algorithm is applied to induction motor drive system controlled FLC-FNN and ANN controller, Also, this paper is proposed the analysis results to verify the effectiveness of the FLC-FNN and ANN controller.

• ETRI Journal
• /
• v.40 no.4
• /
• pp.499-510
• /
• 2018

A vector space based augmented structural kinematic (VSASK) feature descriptor is proposed for human activity recognition. An action descriptor is built by integrating the structural and kinematic properties of the actor using vector space based augmented matrix representation. Using the local or global information separately may not provide sufficient action characteristics. The proposed action descriptor combines both the local (pose) and global (position and velocity) features using augmented matrix schema and thereby increases the robustness of the descriptor. A multiclass support vector machine (SVM) is used to learn each action descriptor for the corresponding activity classification and understanding. The performance of the proposed descriptor is experimentally analyzed using the Weizmann and KTH datasets. The average recognition rate for the Weizmann and KTH datasets is 100% and 99.89%, respectively. The computational time for the proposed descriptor learning is 0.003 seconds, which is an improvement of approximately 1.4% over the existing methods.

• Journal of Engineering Education Research
• /
• v.21 no.1
• /
• pp.14-26
• /
• 2018

The goal of this study was to explore topic defining patterns of students in interdisciplinary Capstone Design Class. Thematic analysis methodology was used to examine 85 Korean college students' lived experience of project topic generation which is for interdisciplinary capstone design class and Individual open-ended survey for constituted the data sources. Findings show four contexts of student's topic defining patterns using thematic analysis including (a) one leader's directed problem representation, (b) team common decision making after brainstorming, (c) empathy with professor proposed issue, (d) problems offered to students by corporate or research competitions. Based on research result, I could suggest instructional strategies of Capstone Design Class of teacher for helping their students' topic defining. It was necessary to minimize the opinions of the instructors at the beginning of class and minimize the number of team members. And also it provided a lot of opportunities to collaborate with companies in the topic selection process, it will help to develop the students' ability to determine the valuable topic in project.