• Convergence Security Journal
• /
• v.20 no.3
• /
• pp.71-78
• /
• 2020

Bitcoin-based blockchain technology provides an infrastructure that enables anonymous smart contracts, low-cost remittances, and online payments. However, the block-chain technology that implements the bitcoin has scalability constraints in tradeoffs between throughput and latency. To solve these problems, the Byzantine fault tolerant block-chain technique has been proposed. This technique improves throughput without increasing latency by selecting a leader and constructing many microblocks that do not contain proofs of work within the existing block by the leader. However, this technique may be less secure than existing techniques in selecting the reader.

• Journal of the Institute of Convergence Signal Processing
• /
• v.2 no.1
• /
• pp.28-37
• /
• 2001

An image retrieval method combining shape information of 2-dimension color histograms with color information of HSI color histograms is proposed in this paper. In addition, the proposed method can find location information of image through the comparison of similarity among subimages. The suggested retrieval method applies the location information to shape and color information and can retrieve region information which is hard to distinguish in the binary image. Some simulation results show that it works very well in the behalf of precision/recall graph compare with conventional method which uses color histogram. Especially, the proposed method brought well effects such as rotations and transitions of the objects in an image was found.

• Journal of the Korea Convergence Society
• /
• v.10 no.4
• /
• pp.39-43
• /
• 2019

The gantry of surface mount equipment (SMD) is responsible for transferring parts from the feeder to the PCB. At this time, the moving time of the gantry affects the yield. Therefore, in this paper, we propose the fastest path from the suction to the mounting to reduce the gantry travel time. This path is a case where the velocity in front of the camera is 2m/sec due to the nature of the gantry. Therefore, the trajectory graph of this case was created through simulation and the travel time was calculated. As a result, we can see that the moving time of the moving-motion method proposed in this paper is 20% shorter than the current stop-motion method.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.1
• /
• pp.109-116
• /
• 2021

Since RDF (Resource Description Framework) triples are modeled as graph, we cannot directly adopt existing solutions in relational databases and XML technology. In order to store, index, and query Linked Data more efficiently, we propose a convergence indexing method combined R*-tree and K-dimensional trees. This method uses a hybrid storage system based on HDD (Hard Disk Drive) and SSD (Solid State Drive) devices, and a separated filter and refinement index structure to filter unnecessary data and further refine the immediate result. We perform performance comparisons based on three standard join retrieval algorithms. The experimental results demonstrate that our method has achieved remarkable performance compared to other existing methods such as Quad and Darq.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.1
• /
• pp.54-60
• /
• 2021

AR (Augmented Reality) is a technology that provides virtual content to the real world and provides additional information to objects in real-time through 3D content. In the past, a high-performance device was required to experience AR, but it was possible to implement AR more easily by improving mobile performance and mounting various sensors such as ToF (Time-of-Flight). Also, the importance of mobile augmented reality is growing with the commercialization of high-speed wireless Internet such as 5G. Thus, this paper proposes a system that can provide AR services via GNN (Graph Neural Network) using cameras and sensors on mobile devices. ToF of mobile devices is used to capture depth maps. A 3D point cloud was created using RGB images to distinguish specific colors of objects. Point clouds created with RGB images and Depth Map perform downsampling for smooth communication between mobile and server. Point clouds sent to the server are used for 3D object detection. The detection process determines the class of objects and uses one point in the 3D bounding box as an anchor point. AR contents are provided through app and web through class and anchor of the detected object.

• Korean Journal of Artificial Intelligence
• /
• v.11 no.4
• /
• pp.15-20
• /
• 2023

Machine learning is comprised of supervised learning, unsupervised learning and reinforcement learning as the type of data and processing mechanism. In this paper, as input and output are unclear and it is difficult to apply the concrete modeling mathematically, reinforcement learning method are applied for crawling robot in this paper. Especially, Q-Learning is the most effective learning technique in model free reinforcement learning. This paper presents a method to implement a crawling robot that is operated by finding the most optimal crawling method through trial and error in a dynamic environment using a Q-learning algorithm. The goal is to perform reinforcement learning to find the optimal two motor angle for the best performance, and finally to maintain the most mature and stable motion about EV3 Crawling robot. In this paper, for the production of the crawling robot, it was produced using Lego Mindstorms with two motors, an ultrasonic sensor, a brick and switches, and EV3 Classroom SW are used for this implementation. By repeating 3 times learning, total 60 data are acquired, and two motor angles vs. crawling distance graph are plotted for the more understanding. Applying the Q-learning reinforcement learning algorithm, it was confirmed that the crawling robot found the optimal motor angle and operated with trained learning, and learn to know the direction for the future research.

• Bulletin of the Korean Mathematical Society
• /
• v.54 no.6
• /
• pp.2043-2051
• /
• 2017

Consider a sequence of compactly supported Hamiltonian diffeomorphisms ${\phi}_k$ of an exact symplectic manifold, all of which are "graphical" in the sense that their graphs are identified by a Darboux-Weinstein chart with the image of a one-form. We show by an elementary argument that if the ${\phi}_k$ $C^0$-converge to the identity, then their Calabi invariants converge to zero. This generalizes a result of Oh, in which the ambient manifold was the two-disk and an additional assumption was made on the Hamiltonians generating the ${\phi}_k$. We discuss connections to the open problem of whether the Calabi homomorphism extends to the Hamiltonian homeomorphism group. The proof is based on a relationship between the Calabi invariant of a $C^0$-small Hamiltonian diffeomorphism and the generalized phase function of its graph.

• Journal of information and communication convergence engineering
• /
• v.6 no.1
• /
• pp.110-116
• /
• 2008

A RFID is an automatic data collection system based on the radio frequency and is the key technology of ubiquitous computing environments. Since the locations of objects attached by RFID tags can be acquired by readers, it is possible to query the locations of tags. To query tags efficiently, the data of RFID tags should be modeled and indexed. However, since the location information of tags, the predicates of queries, are differ from coordinates of moving objects, it is difficult to model tags under the concept of moving objects, In this paper, we propose the location model of tags to represents the trajectories of tags. The location model is composed of the set and graph based approaches.

• Journal of Digital Convergence
• /
• v.7 no.1
• /
• pp.57-71
• /
• 2009

The visualization of business reports has received greater attention from information system scholars. Tables, graph and charts are often used to represent vast amount of complex numerical data and spreadsheet visuals become a de facto standard in business. This study suggests the use of individual's cognitive differences on business report visualization instead of providing "one visual fits all type of reports." It is argued that reports with data augmented by appropriate visuals will affect the efficiency and effectiveness of an individual's learning outcomes and subsequently his or her decision making processes. It is argued here that report visualization can augment the usefulness of contents and enhance many desirable features of reports as specified in those proposed models.

• Journal of information and communication convergence engineering
• /
• v.13 no.2
• /
• pp.113-122
• /
• 2015

Feature subset selection is as a pre-processing step in learning algorithms. In this paper, we propose an efficient algorithm, ModifiedFAST, for feature subset selection. This algorithm is suitable for text datasets, and uses the concept of information gain to remove irrelevant and redundant features. A new optimal value of the threshold for symmetric uncertainty, used to identify relevant features, is found. The thresholds used by previous feature selection algorithms such as FAST, Relief, and CFS were not optimal. It has been proven that the threshold value greatly affects the percentage of selected features and the classification accuracy. A new performance unified metric that combines accuracy and the number of features selected has been proposed and applied in the proposed algorithm. It was experimentally shown that the percentage of selected features obtained by the proposed algorithm was lower than that obtained using existing algorithms in most of the datasets. The effectiveness of our algorithm on the optimal threshold was statistically validated with other algorithms.