• Electronics and Telecommunications Trends
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• v.36 no.2
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• pp.1-11
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• 2021

As sensors such as Inertial Measurement Unit, cameras, and Light Detection and Rangings have become cheaper and smaller, research has been actively conducted to implement functions automating micro aerial vehicles such as multirotor type drones. This would fully enable the autonomous flight of drones in the real world without human intervention. In this article, we present a survey of state-of-the-art development on autonomous drones. To build an autonomous drone, the essential components can be classified into pose estimation, environmental perception, and obstacle-free trajectory generation. To describe the trend, we selected three leading research groups-University of Pennsylvania, ETH Zurich, and Carnegie Mellon University-which have demonstrated impressive experiment results on automating drones using their estimation, perception, and trajectory generation techniques. For each group, we summarize the core of their algorithm and describe how they implemented those in such small-sized drones. Finally, we present our up to date research status on developing an autonomous drone.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.4 no.2
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• pp.369-378
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• 2014

The Reed-Muller code is one of the efficient algorithms for multiple bit error correction, however, its high-computation requirement inherent in the decoding process prohibits its use in practical applications. To solve this problem, this paper proposes a graphics processing unit (GPU)-based parallel error control approach using Reed-Muller R(r, m) coding for real-time wireless communication systems. GPU offers a high-throughput parallel computing platform that can achieve the desired high-performance decoding by exploiting massive parallelism inherent in the algorithm. In addition, we compare the performance of the GPU-based approach with the equivalent sequential approach that runs on the traditional CPU. The experimental results indicate that the proposed GPU-based approach exceedingly outperforms the sequential approach in terms of execution time, yielding over 70× speedup.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.364-380
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• 2016

The most popular approach in object classification is based on the bag of visual-words model, which has several fundamental problems that restricting the performance of this method, such as low time efficiency, the synonym and polysemy of visual words, and the lack of spatial information between visual words. In view of this, an object classification based on weakly supervised E2LSH and saliency map weighting is proposed. Firstly, E2LSH (Exact Euclidean Locality Sensitive Hashing) is employed to generate a group of weakly randomized visual dictionary by clustering SIFT features of the training dataset, and the selecting process of hash functions is effectively supervised inspired by the random forest ideas to reduce the randomcity of E2LSH. Secondly, graph-based visual saliency (GBVS) algorithm is applied to detect the saliency map of different images and weight the visual words according to the saliency prior. Finally, saliency map weighted visual language model is carried out to accomplish object classification. Experimental results datasets of Pascal 2007 and Caltech-256 indicate that the distinguishability of objects is effectively improved and our method is superior to the state-of-the-art object classification methods.

• ETRI Journal
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• v.44 no.4
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• pp.573-587
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• 2022

The agricultural sector is completely different from other sectors since it completely relies on various natural and climatic factors. Climate changes have many effects, including lack of annual rainfall and pests, heat waves, changes in sea level, and global ozone/atmospheric CO₂ fluctuation, on land and agriculture in similar ways. Climate change also affects the environment. Based on these factors, farmers chose their crops to increase productivity in their fields. Many existing agricultural ontologies are either domain-specific or have been created with minimal vocabulary and no proper evaluation framework has been implemented. A new agricultural ontology focused on subdomains is designed to assist farmers using Jaccard relative extractor (JRE) and Naïve Bayes algorithm. The JRE is used to find the similarity between two sentences and words in the agricultural documents and the relationship between two terms is identified via the Naïve Bayes algorithm. In the proposed method, the preprocessing of data is carried out through natural language processing techniques and the tags whose dimensions are reduced are subjected to rule-based formal concept analysis and mapping. The subdomain ontologies of weather, pest, and soil are built separately, and the overall agricultural ontology are built around them. The gold standard for the lexical layer is used to evaluate the proposed technique, and its performance is analyzed by comparing it with different state-of-the-art systems. Precision, recall, F-measure, Matthews correlation coefficient, receiver operating characteristic curve area, and precision-recall curve area are the performance metrics used to analyze the performance. The proposed methodology gives a precision score of 94.40% when compared with the decision tree(83.94%) and K-nearest neighbor algorithm(86.89%) for agricultural ontology construction.

• 기호학연구
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• no.56
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• pp.45-70
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• 2018

Criticism of the postmodern philosophy of the system of representation, which has continued since the Renaissance, is based on a critique of the dichotomy that separates the subjects and objects and the environment from the human being. Interactivity, highlighted in a series of works emerging as postmodern trends in the 1960s, was transmitted to an interactive aspect of digital art in the late 1990s. The key feature of digital art is the possibility of infinite variations reflecting unpredictable changes based on public participation on the spot. In this process, the importance of computer programs is highlighted. Instead of using the existing program as it is, more and more artists are creating and programming their own algorithms or creating unique algorithms through collaborations with programmers. We live in an era of paradigm shift in which programming itself must be considered as a creative act. Simulation technology and VR technology draw attention as a technique to represent the meaning of reality. Simulation technology helps artists create experimental works. In fact, Baudrillard's concept of Simulation defines the other reality that has nothing to do with our reality, rather than a reality that is extremely representative of our reality. His book Simulacra and Simulation refers to the existence of a reality entirely different from the traditional concept of reality. His argument does not concern the problems of right and wrong. There is no metaphysical meaning. Applying the concept of simulation to algorithmic art, the artist models the complex attributes of reality in the digital system. And it aims to build and integrate internal laws that structure and activate the world (specific or individual), that is to say, simulate the world. If the images of the traditional order correspond to the reproduction of the real world, the synthesized images of algorithmic art and simulated space-time are the forms of art that facilitate the experience. The moment of seeing and listening to the work of Ian Cheng presented in this article is a moment of personal experience and the perception is made at that time. It is not a complete and closed process, but a continuous and changing process. It is this active and situational awareness that is required to the audience for the comprehension of post-representation's forms.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1749-1758
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• 1997

This paper suggests the development of dynamic forecasting model for short-term power demand based on Radial Basis Function Network and Pal's GLVQ algorithm. Radial Basis Function methods are often compared with the backpropagation training, feed-forward network, which is the most widely used neural network paradigm. The Radial Basis Function Network is a single hidden layer feed-forward neural network. Each node of the hidden layer has a parameter vector called center. This center is determined by clustering algorithm. Theatments of classical approached to clustering methods include theories by Hartigan(K-means algorithm), Kohonen(Self Organized Feature Maps %3A SOFM and Learning Vector Quantization %3A LVQ model), Carpenter and Grossberg(ART-2 model). In this model, the first approach organizes the load pattern into two clusters by Pal's GLVQ clustering algorithm. The reason of using GLVQ algorithm in this model is that GLVQ algorithm can classify the patterns better than other algorithms. And the second approach forecasts hourly load patterns by radial basis function network which has been constructed two hidden nodes. These nodes are determined from the cluster centers of the GLVQ in first step. This model was applied to forecast the hourly loads on Mar. $4^{th},\;Jun.\;4^{th},\;Jul.\;4^{th},\;Sep.\;4^{th},\;Nov.\;4^{th},$ 1995, after having trained the data for the days from Mar. $1^{th}\;to\;3^{th},\;from\;Jun.\;1^{th}\;to\;3^{th},\;from\;Jul.\;1^{th}\;to\;3^{th},\;from\;Sep.\;1^{th}\;to\;3^{th},\;and\;from\;Nov.\;1^{th}\;to\;3^{th},$ 1995, respectively. In the experiments, the average absolute errors of one-hour ahead forecasts on utility actual data are shown to be 1.3795%.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.2
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• pp.267-277
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• 2017

One of fundamental problems in developing robust distributed services is how to achieve distributed consensus agreeing some data values that should be shared among participants in a distributed service. As one of algorithms for distributed consensus, Raft is known as a simple and understandable algorithm by decomposing the distributed consensus problem into three subproblems(leader election, log replication and safety). But, the algorithm dose not mention any types of dynamic configuration of participant peers such as adding new peers to a consensus group or deleting peers from the group. In this paper, we present a new consensus algorithm named Raft-D, which supports the dynamic configuration of participant peers by extending the Raft algorithm. For this, Raft-D manages the additional information maintained by participant nodes, and provides a technique to check the connection status of the nodes belonging to the consensus group. Based on the technique, Raft-D defines conditions and states to deal with adding new peers to the consensus group or deleting peers from the group. Based on those conditions and states, Raft-D performs the dynamic configuration process for a consensus group through the log update mechanism of the Raft algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1373-1392
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• 2017

WiFi Direct (WD) is a state of the art technology for a Device-to-Device (D2D) communication in 802.11 networks. The performance of the WD system can be significantly affected by some key factors such as the type of application, specifications of MAC and PHY layer parameters, and surrounding environment etc. It is, therefore, important to develop a system model that takes these factors into account. In this paper, we focus on investigating the design parameters of the PHY layer that could maximize the efficiency of the WD 802.11 system. For this purpose, a basic theoretical model is formulated for a WD network under a 2x2 Multiple In Multiple Out (MIMO) TGn channel B model. The design level parameters such as input symbol rate and antenna spacing, as well as the effects of the environment, are thoroughly examined in terms of path gain, spectral density, outage probability and Packet Error Rate (PER). Thereafter, a novel adaptive algorithm is proposed to choose optimal parameters in accordance with the Quality of Experience (QoE) for a targeted application. The simulation results show that the proposed method outperforms the standard method thereby achieving an optimal performance in an adaptive manner.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.2
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• pp.179-185
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• 2015

Although an accelerometer is a sensor that measures acceleration, it cannot be used by itself to measure the acceleration when the orientation of the sensor changes. This paper introduces a Kalman filter for the estimation of a sensor acceleration based on a six-axis inertial sensor (i.e., a three-axis accelerometer and three-axis gyroscope). The novelty of the proposed Kalman filter lies in the fact that its state vector includes not only the tilt angle variable but also the sensor acceleration. Thus, the filter can explicitly estimate the latter with a high accuracy. The accuracy of acceleration estimates were validated experimentally under three different dynamic conditions, using an optical motion capture system. It could be concluded that the performance of the proposed Kalman filter was comparable to that of the state-of-the-art estimation algorithm employed by the Xsens MTw. The proposed algorithm may be more suitable than inertial/magnetic sensor-based algorithms for various applications adopting six-axis inertial sensors.

• Biomaterials and Biomechanics in Bioengineering
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• v.2 no.4
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• pp.249-269
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• 2015

A problem faced by oil companies is the maintenance of the location register of pipelines that cross the surf zone, the regular survey of their location, and also their inspection. A survey of the state of art did not allow identifying operating systems capable of executing such tasks. Commercial technologies available on the market also do not address this problem and/or do not satisfy the presented requirements. A possible solution is to use robotic systems which have the ability to walk on the shore and in the surf zone, subject to existing currents and ripples, and being able to withstand these ambient conditions. In this sense, the authors propose the development of a spider crab biologically inspired robot to achieve those tasks. Based on these ideas, this work presents a biomechanical study of the spider crab, its modeling and simulation using the SimMechanics toolbox of Matlab/Simulink, which is the first phase of this more vast project. Results show a robot model that is moving in an "animal like" manner, the locomotion, the algorithm presented in this paper allows the crab to walk sideways, in the desired direction.