• International Journal of Aeronautical and Space Sciences
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• v.13 no.1
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• pp.64-73
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• 2012

Pointing stability of high precision observation satellites must satisfy the stringent requirements to perform at a designed level. As even a small vibrational disturbance can result in severe degradation of the optical performance, the effects of inorbit vibrational environment on the performance of optical payload must be predicted and analyzed in the design phase in order to ensure that the requirements imposed on the payload are fully met. In this paper, an integrated framework for the evaluation of the performance of optical payloads is developed. The developed simulation tool comprises of the reaction wheel induced disturbance model, state space model of a structure in modal form and Cassegrain reflector model. The performance degradation of the optical system due to jitter is expressed by using modulation transfer function (MTF) and image simulation. Moreover, vibration isolator model is also added to show the effectiveness of using a vibration isolator for the elimination of the effects of jitter in the acquisition of an image.

• Smart Media Journal
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• v.5 no.1
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• pp.30-37
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• 2016

In recent decades, the study of human brain function has dramatically increased thanks to the advent of Functional Magnetic Resonance Imaging. This is a powerful tool which provides a deep view of the activities of the brain. From fMRI data, the neuroscientists analyze which parts of the brain have responsibility for a particular action and finding the common pattern representing each state involved in these tasks. This is one of the most challenges in neuroscience area because of noisy, sparsity of data as well as the differences of anatomical brain structure of each person. In this paper, we propose the use of appropriate discriminant methods, such as Fisher Discriminant Ratio and hypothesis testing, together with strong boosting ability of Adaboost classifier. We prove that discriminant methods are effective in classifying cognitive states. The experiment results show significant better accuracy than previous works. We also show that it is possible to train a successful classifier without prior anatomical knowledge and use only a small number of features.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.379-379
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• 2010

Recent technical advances in OLEDs (organic light emitting devices) requires more and more the improvement in low operation voltage, long lifetime, and high luminance efficiency. Inverted top emission OLEDs (ITOLED) appeared to overcome these problems. This evolved to operate better luminance efficiency from conventional OLEDs. First, it has large open area so to be brighter than conventional OLEDs. Also easy integration is possible with Si-based driving circuits for active matrix OLED. But, a proper buffer layer for carrier injection is needed in order to get a good performance. The buffer layer protects underlying organic materials against destructive particles during the electrode deposition and improves their charge transport efficiency by reducing the charge injection barrier. Hexaazatriphenylene-hexacarbonitrile (HAT-CN), a discoid organic molecule, has been used successfully in tandem OLEDs due to its high workfunction more than 6.1 eV. And it has the lowest unoccupied molecular orbital (LUMO) level near to Fermi level. So it plays like a strong electron acceptor. In this experiment, we measured energy level alignment and hole current density on inverted OLED structures for hole injection. The normal film structure of Al/NPB/ITO showed bad characteristics while the HAT-CN insertion between Al and NPB greatly improved hole current density. The behavior can be explained by charge generation at the HAT-CN/NPB interface and gap state formation at Al/HAT-CN interface, respectively. This result indicates that a proper organic buffer layer can be successfully utilized to enhance hole injection efficiency even with low work function Al anode.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.55-55
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• 2010

We use ab initio density functional theory to determine the effect of bundling on the equilibrium structure, electronic and magnetic properties of $Mo_6S_{9-x}I_x$nanowires with x = 0, 3, 4.5, 6. Each unit cell of these systems contains two $Mo_6S_{6-x}I_x$ clusters connected by S3 linkages to form an ordered linear array. Due to the bi-stability of the sulfur linkages, the total energy of the nanowires exhibits typically many minima as a function of the wire length. We find that nanowires can switch over from metallic to semiconducting by applying axial stress. Structural order is expected in bundles with x=0 and x=6, since there is no disorder in the decoration of the Mo clusters. In bundles with other stoichiometries, we expect structural disorder to occur. We find the optimum inter-wire distance to depend sensitively on the orientation of the wires, but only weakly on x. It is also found that the electronic properties of nanowires are affected strongly due to bundling of nanowires exhibiting very unusual Fermi surfaces. Furthermore, ferromagnetic behaviors are observed in selected stable and many more unstable atomic arrangements in nanowire bundles.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.6
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• pp.419-427
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• 2014

Nonlinear features of ultrasonic waves are more sensitive to the presence of a fatigue crack than their linear counterparts are. For this reason, the use of nonlinear ultrasonic techniques to detect a fatigue crack at its early stage has been widely investigated. Of the different proposed techniques, laser nonlinear wave modulation spectroscopy (LNWMS) is unique because a pulse laser is used to exert a single broadband input and a noncontact measurement can be performed. Broadband excitation causes a nonlinear source to exhibit modulation at multiple spectral peaks owing to interactions among various input frequency components. A feature called maximum sideband peak count difference (MSPCD), which is extracted from the spectral plot, measures the degree of crack-induced material nonlinearity. First, the ratios of spectral peaks whose amplitudes are above a moving threshold to the total number of peaks are computed for spectral signals obtained from the pristine and the current state of a target structure. Then, the difference of these ratios are computed as a function of the moving threshold. Finally, the MSPCD is defined as the maximum difference between these ratios. The basic premise is that the MSPCD will increase as the nonlinearity of the material increases. This technique has been used successfully for localizing fatigue cracks in metallic plates.

• Journal of Magnetics
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• v.16 no.1
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• pp.74-76
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• 2011

Interior permanent-magnet synchronous motors (IPMSMs) produce both magnetic and reluctance torques. The reluctance torque is due to the difference between the d- and q-axis inductances based on the geometric rotor structure. The steady-state performance analysis and precise control of the IPMSMs greatly depend on the accurate determination of the parameters. The three essential parameters of the IPMSMs are the armature flux linkage of the permanent magnet, the d-axis inductance, and the q-axis inductance. In the basic design step of an IPMSM, the inductance parameters are very important for determining the motor characteristics, such as the input voltage, torque, and efficiency. Thus, it is very important to accurately estimate the values of the motor inductances. The inductance parameters of IPMSMs have nonlinear characteristics along the magnet size because the iron core is saturated by the magnet and armature reaction fluxes. In this study, the inductance parameters were calculated using both the magnetic-equivalent-circuit method and the finite-element method (FEM). Then the calculated parameters were compensated by the saturation coefficient function, which was also calculated via the magnetic-equivalent-circuit method and FEM.

• Bulletin of the Korean Chemical Society
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• v.6 no.6
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• pp.344-347
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• 1985

Perovskite type oxides of $SrTiO_3,SrZrO_3,and\;SrTi_{1-x}Zr_xO_3$ have been systematically synthesized at $1250^{\circ}C$and $1550^{\circ}C$ with specimens containing additions of up to x=0.9 of zirconium by solid state reactions and characterized by X-ray diffraction. X-ray diffraction studies showed that the compound $SrTi_{1-x}Zr_xO_3$ has cubic structure. The lattice paramters of $SrTi_{1-x}Zr_xO_3$ solid solutions obey the Vegard's law and fairly large increase in volume can acompany the formation of this solution with increasing Zr content(X). Assuming the lattice constants of perovskite type compounds $A(B_{1-x}B'_x)O_3$where $B_{1-x}B'_x$ is $Ti_{1-x}Zr_x$, to be a linear function of the ionic radii of B and B' ions, the disordered ion pair of $Ti^{4+}$and $Zr^{4+}$ was verified from the lattice constants of a series compounds varying x=0,0.05, 0.25, 0.5, 0.75, 0.9, and 1.0 with known isovalent pairs.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.97-106
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• 2021

Social networking platforms have become a smart way for people to interact and meet on internet. It provides a way to keep in touch with friends, families, colleagues, business partners, and many more. Among the various social networking sites, Twitter is one of the fastest-growing sites where users can read the news, share ideas, discuss issues etc. Due to its vast popularity, the accounts of legitimate users are vulnerable to the large number of threats. Spam and Malware are some of the most affecting threats found on Twitter. Therefore, in order to enjoy seamless services it is required to secure Twitter against malicious users by fixing them in advance. Various researches have used many Machine Learning (ML) based approaches to detect spammers on Twitter. This research aims to devise a secure system based on Hybrid Similarity Cosine and Soft Cosine measured in combination with Genetic Algorithm (GA) and Artificial Neural Network (ANN) to secure Twitter network against spammers. The similarity among tweets is determined using Cosine with Soft Cosine which has been applied on the Twitter dataset. GA has been utilized to enhance training with minimum training error by selecting the best suitable features according to the designed fitness function. The tweets have been classified as spammer and non-spammer based on ANN structure along with the voting rule. The True Positive Rate (TPR), False Positive Rate (FPR) and Classification Accuracy are considered as the evaluation parameter to evaluate the performance of system designed in this research. The simulation results reveals that our proposed model outperform the existing state-of-arts.

• Journal of Korean Vacuum Science & Technology
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• v.6 no.1
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• pp.12-15
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• 2002

The physical properties, including magneto-optical and transport ones, of Ni$_2$MnG$_2$ alloy in the martensitic and austenitic states were investigated. The dependence of the temperature coefficient of resistivity on temperature shows kinks at the structural and ferro-para magnetic transitions. Electron-magnon and electron-phonon scattering are analyzed to be the dominant scattering mechanisms of the Ni$_2$MnG$_2$ alloy in the martensitic and austenitic states, respectively. The experimental real parts of the off-diagonal components of the dielectric function present two sharp peaks, one at 1.9 eV and the other at 3.2 eV, and a broad shoulder at 3.5 eV, all are identified by the band-structure calculations. These peak positions are coincident with those in the corresponding optical-conductivity spectrum, which is thought to originate from the single-spin state in Ni$_2$MnG$_2$ alloy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.97-119
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• 2023

The number of industrial Internet of Things (IoT) users is increasing rapidly. Lightweight block ciphers have started to be used to protect the privacy of users. Hardware-oriented security design should fully consider the use of fewer hardware devices when the function is fully realized. Thus, this paper designs a lightweight block cipher IIoTBC for industrial IoT security. IIoTBC system structure is variable and flexibly adapts to nodes with different security requirements. This paper proposes a 4×4 S-box that achieves a good balance between area overhead and cryptographic properties. In addition, this paper proposes a preprocessing method for 4×4 S-box logic gate expressions, which makes it easier to obtain better area, running time, and power data in ASIC implementation. Applying it to 14 classic lightweight block cipher S-boxes, the results show that is feasible. A series of performance tests and security evaluations were performed on the IIoTBC. As shown by experiments and data comparisons, IIoTBC is compact and secure in industrial IoT sensor nodes. Finally, IIoTBC has been implemented on a temperature state acquisition platform to simulate encrypted transmission of temperature in an industrial environment.