• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.4
• /
• pp.637-644
• /
• 2019

This paper describes an implementation of a graph-based simultaneous localization and mapping(SLAM) method called the General Graph Optimization. The General Graph Optimization formulates the SLAM problem using nodes and edges. The nodes represent the location and attitude of a robot in time sequence, and the edge between the nodes depict the constraint between the nodes. The constraints are imposed by sensor measurements. The General Graph Optimization solves the problem by optimizing the performance index determined by the constraints. The implementation is verified using the measurement data sets which are open for test of various SLAM methods.

• Smart Structures and Systems
• /
• v.24 no.2
• /
• pp.257-266
• /
• 2019

The benefit of data fusion in improving the performance of Higher Order Sliding Mode (HOSM) observer is brought out in this paper. This improvement in the performance of HOSM observer, resulted in the improvement of active vibration control of a piezo actuated structure, when controlled by a Discrete Sliding Mode Controller (DSMC). The structure is embedded with two piezo sensors for measuring the first two vibrating modes. The fused output of sensors is applied to the HOSM observer for generating state estimates, these states generated are applied to the DSMC, designed for the fourth order linear time invariant model of the structure. In the simulation study, the structure is excited at the first and second mode resonance. It is found that better vibration suppression is obtained, when the states generated by the fused output of sensors is applied as controller input, than the vibration suppression obtained by applying the states generated by using individual sensor output. The closed loop performance of DSMC obtained with HOSM observer is compared with the closed loop performance obtained with the conventional observer. Results obtained shows that better vibration suppression is obtained when the states generated by HOSM observer is applied as controller input.

• Advances in aircraft and spacecraft science
• /
• v.6 no.5
• /
• pp.349-369
• /
• 2019

In the design of flight control systems there are issues that deserve special consideration and attention such as external perturbations or systems failures. A Simple Adaptive Controller (SAC) that does not require a-priori knowledge of the faults is proposed in this paper with the aim of realizing a fault tolerant flight control system capable of leading the pitch motion of an aircraft. The main condition for obtaining a stable adaptive controller is the passivity of the plant; however, since real systems generally do not satisfy such requirement, a properly defined Parallel Feedforward Compensator (PFC) is used to let the augmented system meet the passivity condition. The design approach used in this paper to synthesize the PFC and to tune the invariant gains of the SAC is the Population Decline Swarm Optimization ($P_DSO$). It is a modification of the Particle Swarm Optimization (PSO) technique that takes into account a decline demographic model to speed up the optimization procedure. Tuning and flight mechanics results are presented to show both the effectiveness of the proposed $P_DSO$ and the fault tolerant capability of the proposed scheme to control the aircraft pitch motion even in presence of elevator failures.

• Journal of Information Processing Systems
• /
• v.15 no.4
• /
• pp.737-747
• /
• 2019

Shape description is an important and fundamental issue in content-based image retrieval (CBIR), and a number of shape description methods have been reported in the literature. For shape description, both global information and local contour variations play important roles. In this paper a new included-angular ternary pattern (IATP) based shape descriptor is proposed for shape image retrieval. For each point on the shape contour, IATP is derived from its neighbor points, and IATP has good properties for shape description. IATP is intrinsically invariant to rotation, translation and scaling. To enhance the description capability, multiscale IATP histogram is presented to describe both local and global information of shape. Then multiscale IATP histogram is combined with included-angular histogram for efficient shape retrieval. In the matching stage, cosine distance is used to measure shape features' similarity. Image retrieval experiments are conducted on the standard MPEG-7 shape database and Swedish leaf database. And the shape image retrieval performance of the proposed method is compared with other shape descriptors using the standard evaluation method. The experimental results of shape retrieval indicate that the proposed method reaches higher precision at the same recall value compared with other description method.

• The Bulletin of The Korean Astronomical Society
• /
• v.43 no.2
• /
• pp.40.4-41
• /
• 2018

The current 'standard model' of cosmology provides a minimal theoretical framework that can explain the gaussian, nearly scale-invariant density perturbations observed in the CMB to the late time clustering of galaxies. However accepting this framework, requires that we include within our cosmic inventory a vacuum energy that is ~122 orders of magnitude lower than Quantum Mechanical predictions, or alternatively a new scalar field (dark energy) that has negative pressure. An alternative approach to adding extra components to the Universe would be to modify the equations of Gravity. Although GR is supported by many current observations there are still alternative models that can be considered. Recently there have been many works attempting to test for modified gravity using the large scale clustering of galaxies, ISW, cluster abundance, RSD, 21cm observations, and weak lensing. In this work, we compare various modified gravity models using cosmic shear data from the Deep Lens Survey as well as data from CMB, SNe Ia, and BAO. We use the Bayesian Evidence to quantify the comparison robustly, which naturally penalizes complex models with weak data support. In this talk we present our methodology and preliminary results that show f(R) gravity is mildly disfavoured by the data.

• Journal of Distribution Science
• /
• v.18 no.12
• /
• pp.67-77
• /
• 2020

Purpose: Based on the author's adapted invariant choice, this study is to present the methodology and the calculation of the integral index of the digital component of the quality of life. By analyzing the digital indexes, the study is also to discuss distribution of ICT and the digital quality of life of the population of Kazakhstan and its regions. Research design, data, methodology: In this research, the method of calculation of integral assessment of the indicator was used, which indicates index constructs. The study analyzed objective secondary data for the period 2017-2019, which was the database from official websites of the Committee on Statistics of the Republic of Kazakhstan. Results: The study produced an integral code for assessing digital components of living standards of the population, consisting of five groups sub-indexes. Conclusions: Based on the provided analyses, we can confirm the existence of a significant difference of all the indicators of digital living standards of the population between the two leading cities: Almaty city and Nur-Sultan city. Furthermore we can deduce the differences of the examined indexes for other regions of Kazakhstan. Despite the rapid adoption of digital technologies, Kazakhstan still has significant digital gaps among cities indicating regional differences in the speed of implementation and distribution of digital technologies.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.5
• /
• pp.1590-1609
• /
• 2021

Laughter is one of the most important nonverbal sound that human generates. It is a means for expressing his emotions. The acoustic and contextual features of this specific sound are different from those of speech and many difficulties arise during their modeling process. During this work, we propose an audio laughter generation system based on unsupervised generative models: the autoencoder (AE) and its variants. This procedure is the association of three main sub-process, (1) the analysis which consist of extracting the log magnitude spectrogram from the laughter database, (2) the generative models training, (3) the synthesis stage which incorporate the involvement of an intermediate mechanism: the vocoder. To improve the synthesis quality, we suggest two hybrid models (LSTM-VAE, GRU-VAE and CNN-VAE) that combine the representation learning capacity of variational autoencoder (VAE) with the temporal modelling ability of a long short-term memory RNN (LSTM) and the CNN ability to learn invariant features. To figure out the performance of our proposed audio laughter generation process, objective evaluation (RMSE) and a perceptual audio quality test (listening test) were conducted. According to these evaluation metrics, we can show that the GRU-VAE outperforms the other VAE models.

• Journal of the Korean Mathematical Society
• /
• v.58 no.1
• /
• pp.123-132
• /
• 2021

Let K be a number field and L a finite abelian extension of K. Let E be an elliptic curve defined over K. The restriction of scalars ResKLE decomposes (up to isogeny) into abelian varieties over K $$Res^L_KE{\sim}{\bigoplus_{F{\in}S}}A_F,$$ where S is the set of cyclic extensions of K in L. It is known that if L is a quadratic extension, then AL is the quadratic twist of E. In this paper, we consider the case that K is a number field containing a primitive third root of unity, $L=K({\sqrt[3]{D}})$ is the cyclic cubic extension of K for some D ∈ K×/(K×)3, E = Ea : y2 = x3 + a is an elliptic curve with j-invariant 0 defined over K, and EaD : y2 = x3 + aD2 is the cubic twist of Ea. In this case, we prove AL is isogenous over K to $E_a^D{\times}E_a^{D^2}$ and a property of the Selmer rank of AL, which is a cubic analogue of a theorem of Mazur and Rubin on quadratic twists.

• Structural Monitoring and Maintenance
• /
• v.7 no.4
• /
• pp.283-294
• /
• 2020

In this paper, an adaptive MEMD based modal identification technique for linear time-invariant systems is proposed employing multiple vibration measurements. Traditional empirical mode decomposition (EMD) suffers from mode-mixing during sifting operations to identify intrinsic mode functions (IMF). MEMD performs better in this context as it considers multi-channel data and projects them into a n-dimensional hypercube to evaluate the IMFs. Using this technique, modal parameters of the structural system are identified. It is observed that MEMD has superior performance compared to its traditional counterpart. However, it still suffers from mild mode-mixing in higher modes where the energy contents are low. To avoid this problem, an adaptive filtering scheme is proposed to decompose the interfering modes. The Proposed modified scheme is then applied to vibrations of a reinforced concrete road bridge. Results presented in this study show that the proposed MEMD based approach coupled with the filtering technique can effectively identify the parameters of the dominant modes present in the structural response with a significant level of accuracy.

• Journal of the Korean Society of Industry Convergence
• /
• v.24 no.6_1
• /
• pp.693-698
• /
• 2021

As technology advances, there is increasing need for research in different fields where this technology is applied. On of the most researched topic in computer vision is Human activity recognition (HAR), which has widely been implemented in various fields which include healthcare, video surveillance and education. We therefore present in this paper a human activity recognition system based on scale and rotation while employing the Kinect depth sensors to obtain the human skeleton joints. In contrast to previous approaches that use joint angles, in this paper we propose that each limb has an angle with the X, Y, Z axes which we employ as feature vectors. The use of the joint angles makes our system scale invariant. We further calculate the body relative direction in the egocentric coordinates in order to provide the rotation invariance. For the system parameters, we employ 8 limbs with their corresponding angles each having the X, Y, Z axes from the coordinate system as feature vectors. The extracted features are finally trained and tested with the Long short term memory (LSTM) Network which gives us an average accuracy of 98.3%.