Journal of the Korea Institute of Information Security & Cryptology
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v.27
no.3
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pp.439-448
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2017
It is news from nowhere that post-quantum cryptography has side-channel analysis vulnerability. Side-channel analysis attack method and countermeasures for code-based McEliece cryptosystem and lattice-based NTRU cryptosystem have been investigated. Unfortunately, the investigation of the ring-LWE cryptosystem in terms of side-channel analysis is as yet insufficient. In this paper, we propose a chosen ciphertext simple power analysis attack that can be applied when ring-LWE cryptography operates on 8-bit devices. Our proposed attack can recover the key only with [$log_2q$] traces. q is a parameter related to the security level. It is used 7681 and 12289 to match the common 128 and 256-bit security levels, respectively. We identify the vulnerability through experiment that can reveal the secret key in modular add while the ring-LWE decryption performed on real 8-bit devices. We also discuss the attack that uses a similarity measurement method for two vectors to reduce attack time.
Many companies have recently become interested in using social networking sites such as Twitter and Facebook as a new channel to communicate with their customers. For example, companies often offer "special deals" (e.g., coupons, discounts, free samples, etc.) to their customers who participate in promotions or events on social networking sites. Companies often make important announcements on their products or services on social networking sites. By doing so, customers are encouraged to continue to have relationships with companies on social networking sites and to recommend the companies' presence on social networking sites to other potential customers. Moreover, customers who keep close relationships with companies on social networking sites often provide the companies with valuable suggestions and feedback. For instance, Starbucks has more than 2 million followers on Twitter, and often receive suggestions and feedback for their product offerings and services from the followers on Twitter. Although companies realize potential benefits of using social networking sites as a channel to communicate with their customers, it appears that many companies have difficulty forging long-lasting relationships with customers on social networking sites. It is often reported that many customers who had followed companies on Twitter later stopped following them for various reasons. Therefore, it is an important issue to understand what motivates customers to continue to keep relationships with companies on social networking sites. Nonetheless, due attention has yet paid to this issue until recently. This study intends to contribute to our understanding on customers' intention to continue to follow companies on Twitter and to spread positive word-of-mouth about companies on Twitter. Specifically, we identify seven potential factors that customers perceive as important in evaluating their experience with companies on Twitter. The seven factors include similarity, receptivity, interactivity, ubiquitous connectivity, enjoyment, usefulness and transparency. We posit that the seven perception factors can affect the two types of satisfaction, emotional and cognitive, which can in turn influence on customers' intention to follow companies on Twitter and to spread positive word-of-mouth about companies on Twitter. Research hypotheses formulated in this study were tested with data collected from a questionnaire survey administered to customers who had been following companies on Twitter. The data was analyzed with the partial least square (PLS) approach to structural equation modeling. The results of data analysis based on 177 usable responses were generally supportive of our predictions for the effects of the seven factors identified and the two types of satisfaction. In particular, out results suggest that emotional satisfaction was strongly influenced by perceived similarity, perceived receptivity, perceived enjoyment, and perceived transparency. Cognitive satisfaction was significantly influenced by perceived similarity, perceived interactivity, perceived enjoyment, and perceived transparency. While cognitive satisfaction was found to have significant and positive effects on both continued following and word-of-mouth intentions, emotional satisfaction had a significant and positive effect only on word-of-mouth intention.
Introduction: Detrended fluctuation analysis (DFA) is used as a way of studying nonlinearity of EEG. In this study, DFA is applied on sleep EEG of normal subjects to look into its nonlinearity in terms of EEG channels and sleep stages. Method: Twelve healthy young subjects (age:$23.8{\pm}2.5$ years old, male:female=7:5) have undergone nocturnal polysomnography (nPSG). EEG from nPSG was classified in terms of its channels and sleep stages and was analyzed by DFA. Scaling exponents (SEs) yielded by DFA were compared using linear mixed model analysis. Results: Scaling exponents (SEs) of sleep EEG were distributed around 1 showing long term temporal correlation and self-similarity. SE of C3 channel was bigger than that of O1 channel. As sleep stage progressed from stage 1 to slow wave sleep, SE increased accordingly. SE of stage REM sleep did not show significant difference when compared with that of stage 1 sleep. Conclusion: SEs of Normal sleep EEG showed nonlinear characteristic with scale-free fluctuation, long-range temporal correlation, self-similarity and self-organized criticality. SE from DFA differentiated sleep stages and EEG channels. It can be a useful tool in the research with sleep EEG.
Soolo, Kim;Jong-Sung, Choi;Ho-Goon, Yoon;Sang-Wook, Kim
Tunnel and Underground Space
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v.32
no.6
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pp.451-463
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2022
Whenever a mineshaft accidentally collapses, speedy risk assessment is both required and crucial. But onsite safety diagnosis by humans is reportedly difficult considering the additional risk of collapse of the unstable mineshaft. Generally, drones equipped with high-speed lidar sensors can be used for such inspection. However, the drone technology is restrictively applicable at very shallow depth, failing in mineshafts with depths of hundreds of meters because of the limit of wireless communication and turbulence inside the mineshaft. In previous study, a three-dimensional (3D) scanning system with a single channel lidar was fabricated and operated using towed cable in a mineshaft to a depth of 200 m. The rotation and pendulum movement errors of the measuring unit were compensated for by applying the data of inertial measuring unit and comparing the similarity between the scan data of the adjacent depths (Kim et al., 2020). However, the errors grew with scan depth. In this paper, a multi-channel lidar sensor to obtain a continuous cross-sectional image of the mineshaft from a winch system pulled from bottom upward. In this new approach, within overlapped region viewed by the multi-channel lidar, rotation error was compensated for by comparing the similarity between the scan data at the same depth. The fabricated system was applied to scan 0-165 m depth of the mineshaft with 180 m depth. The reconstructed image was depicted in a 3D graph for interpretation.
Carbon materials were synthesized by pyrolysis from fibers of Corn-straw (Zea mays), Rice-straw (Oryza sativa), Jute-straw (Corchorus capsularis) Bamboo (Bombax bambusa), Bagass (Saccharum officinarum), Cotton (Bombax malabaricum), and Coconut (Cocos nucifera); these materials were characterized by scanning electron microscope, X-ray diffraction (XRD), and Raman spectra. All carbon materials are micro sized with large pores or channel like morphology. The unique complex spongy, porous and channel like structure of Carbon shows a lot of similarity with the original anatomy of the plant fibers used as precursor. Waxy contents like tyloses and pits present on fiber tracheids that were seen in the inherent anatomy disappear after pyrolysis and only the carbon skeleton remained; XRD analysis shows that carbon shows the development of a (002) plane, with the exception of carbon obtained from bamboo, which shows a very crystalline character. Raman studies of all carbon materials showed the presence of G- and D-bands of almost equal intensities, suggesting the presence of graphitic carbon as well as a disordered graphitic structure. Carbon materials possessing lesser density, larger surface area, more graphitic with less of an $sp^3$ carbon contribution, and having pore sizes around $10{\mu}m$ favor hydrogen adsorption. Carbon materials synthesized from bagass meet these requirements most effectively, followed by cotton fiber, which was more effective than the carbon synthesized from the other plant fibers.
Journal of the Korean Institute of Telematics and Electronics B
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v.31B
no.8
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pp.74-86
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1994
In this paper a hierarchical stereo matching algorithm to obtain the disparity in wavelet transformed domain by using locally adaptive window and weights is proposed. The pyramidal structure obtained by wavelet transform is used to solve the loss of information which the conventional Gaussian or Laplacian pyramid have. The wavelet transformed images are decomposed into the blurred image the horizontal edges the vertical edges and the diagonal edges. The similarity between each wavelet channel of left and right image determines the relative importance of each primitive and make the algorithm perform the area-based and feature-based matching adaptively. The wavelet transform can extract the features that have the dense resolution as well as can avoid the duplication or loss of information. Meanwhile the variable window that needs to obtain precise and stable estimation of correspondense is decided adaptively from the disparities estimated in coarse resolution and LL(low-low) channel of wavelet transformed stereo image. Also a new relaxation algorithm that can reduce the false match without the blurring of the disparity edge is proposed. The experimental results for various images show that the proposed algorithm has good perfpormance even if the images used in experiments have the unfavorable conditions.
KSII Transactions on Internet and Information Systems (TIIS)
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v.16
no.8
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pp.2552-2570
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2022
Underwater images usually have various problems, such as the color cast of underwater images due to the attenuation of different lights in water, the darkness of image caused by the lack of light underwater, and the haze effect of underwater images because of the scattering of light. To address the above problems, the channel attention mechanism, strengthen-operate-subtract (SOS) boosting mechanism and gated fusion module are introduced in our paper, based on which, an underwater image recovery network is proposed. First, for the color cast problem of underwater images, the channel attention mechanism is incorporated in our model, which can well alleviate the color cast of underwater images. Second, as for the darkness of underwater images, the similarity between the target underwater image after dehazing and color correcting, and the image output by our model is used as the loss function, so as to increase the brightness of the underwater image. Finally, we employ the SOS boosting module to eliminate the haze effect of underwater images. Moreover, experiments were carried out to evaluate the performance of our model. The qualitative analysis results show that our method can be applied to effectively recover the underwater images, which outperformed most methods for comparison according to various criteria in the quantitative analysis.
In middle- and long-distance imaging systems, due to the atmospheric turbulence caused by temperature, wind speed, humidity, and so on, light waves propagating in the air are distorted, resulting in image-quality degradation such as geometric deformation and fuzziness. In remote sensing, astronomical observation, and traffic monitoring, image information loss due to degradation causes huge losses, so effective restoration of degraded images is very important. To restore images degraded by atmospheric turbulence, an image-restoration method based on improved compound multibranch feature fusion (CMFNetPro) was proposed. Based on the CMFNet network, an efficient channel-attention mechanism was used to replace the channel-attention mechanism to improve image quality and network efficiency. In the experiment, two-dimensional random distortion vector fields were used to construct two turbulent datasets with different degrees of distortion, based on the Google Landmarks Dataset v2 dataset. The experimental results showed that compared to the CMFNet, DeblurGAN-v2, and MIMO-UNet models, the proposed CMFNetPro network achieves better performance in both quality and training cost of turbulent-image restoration. In the mixed training, CMFNetPro was 1.2391 dB (weak turbulence), 0.8602 dB (strong turbulence) respectively higher in terms of peak signal-to-noise ratio and 0.0015 (weak turbulence), 0.0136 (strong turbulence) respectively higher in terms of structure similarity compared to CMFNet. CMFNetPro was 14.4 hours faster compared to the CMFNet. This provides a feasible scheme for turbulent-image restoration based on deep learning.
KSCE Journal of Civil and Environmental Engineering Research
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v.29
no.3B
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pp.311-317
/
2009
Similarity indices between sampling sites are calculated and cluster analysis of fish community is carried out by UPGMA based on investigating fish fauna and water environment. The restoration indicators as target species of Wonju stream are selected Cottus poecilopus, Zacco temmincki, and Zacco platypus along upper, middle, and lower streams, respectively. For better habitat suitability, low flow increasing and induced water quality improving must be secured by sewer system rearrangement and watershed management. Composite habitat suitability of Zacco temmincki as target species at middle stream of Wonju stream improve significantly by low flow increasing, which is very important factor to improve habitat suitability. The changes of hydraulics of depth and velocity govern the habitat suitability in general, but the effects are not significant. Low flow increasing with the change of 10% reducing of lower channel improves the composite habitat suitability of 0.37~0.78 to their origin of 0.1~0.25, which represent the channel restoration scheme of Wonju stream for enhancing the habitat suitability of fish community.
The Journal of the Korea institute of electronic communication sciences
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v.15
no.5
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pp.981-986
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2020
The Internet of Things refers to a space-of-things connection network configured to allow things with built-in sensors and communication functions to interact with people and other things, regardless of the restriction of place or time.IoT is a network developed for the purpose of services for human convenience, but the scope of its use is expanding across industries such as power transmission, energy management, and factory automation. However, the communication protocol of IoT, MQTT, is a lightweight message transmission protocol based on the push technology and has a security vulnerability, and this suggests that there are risks such as personal information infringement or industrial information leakage. To solve this problem, we designed a synchronous MQTT security channel that creates a secure channel by using the characteristic that different chaotic dynamical systems are synchronized with arbitrary values in the lightweight message transmission MQTT protocol. The communication channel we designed is a method of transmitting information to the noise channel by using characteristics such as random number similarity of chaotic signals, sensitivity to initial value, and reproducibility of signals. The encryption method synchronized with the proposed key value is a method optimized for the lightweight message transmission protocol, and if applied to the MQTT of IoT, it is believed to be effective in creating a secure channel.
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