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REFERENCES ․이 경 석 ․이 진 호 ․김 창 영 Understanding the Electronic Structures of Solids Hanyoung RYU, Kyoungseok LEE, Jinho LEE and Changyoung KIM Materials often possess various physical properties, and these ...doi:10.3938/phit.26.004 fatcat:az6kfmamufg7ratxx5n4gzxrcm
Security professionals, government agencies, and corporate organizations have found an inherent need to prevent or mitigate attacks from insider threats. Accordingly, active research on insider threat detection has been conducted to prevent and mitigate adverse effects such as leakage of valuable information that may be caused by insiders. Along with the growth of Internet-of-Things (IoT), new security challenges arise in the existing security frameworks. Attack surfaces are significantlydoi:10.1109/access.2020.2990195 fatcat:uxydn6lk4vdi5mtqaotp35s3oq
more »... ed which could cause a severe risk in terms of company insider threat management. In this work, we provide a generalization of aspects of insider threats with IoT and analyze the surveyed literature based on both private and public sources. We then examine data sources considering IoT environments based on the characteristics and the structure of IoT (perceptual, network, and application layers). The result of reviewing the study shows that using the data source of the network and application layer is more suitable than the perceptual layer in the IoT environment. We also categorized each layer's data sources according to their features, and we investigated research objectives and methods for each category. Finally, the potential for utilization and limitations under the IoT environment are presented at the end of each layer examination. INDEX TERMS Insider threat detection, Internet-of-Things, dataset, survey. VOLUME 8, 2020 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
Climate of the Past
<p><strong>Abstract.</strong> Understanding processes controlling the atmospheric methane (CH<sub>4</sub>) mixing ratio is crucial to predict and mitigate future climate changes in this gas. Despite recent detailed studies of the last ∼ <span class="thinspace"></span>1000 to 2000 years, the mechanisms that control atmospheric CH<sub>4</sub> still remain unclear, partly because the late Holocene CH<sub>4</sub> budget may be comprised of both natural and anthropogenic emissions. In contrast, thedoi:10.5194/cp-13-1227-2017 fatcat:sqce3b54irg3vjegfxr2c5x6pq
more »... arly Holocene was a period when human influence was substantially smaller, allowing us to elucidate more clearly the natural controls under interglacial conditions more clearly. Here we present new high-resolution CH<sub>4</sub> records from Siple Dome, Antarctica, covering from 11.6 to 7.7 thousands of years before 1950<span class="thinspace"></span>AD (ka). We observe four local CH<sub>4</sub> minima on a roughly 1000-year spacing, which correspond to cool periods in Greenland. We hypothesize that the cooling in Greenland forced the Intertropical Convergence Zone (ITCZ) to migrate southward, reducing rainfall in northern tropical wetlands. The inter-polar difference (IPD) of CH<sub>4</sub> shows a gradual increase from the onset of the Holocene to ∼ <span class="thinspace"></span>9.5<span class="thinspace"></span>ka, which implies growth of boreal source strength following the climate warming in the northern extratropics during that period.</p>
Understanding the atmospheric methane (CH<sub>4</sub>) change is crucial to predict and mitigate the future climate change. In spite of recent studies using various approaches for the last ~&thinsp;1000 to 2000 years, control mechanisms of CH<sub>4</sub> still remain unclear, partly because the late Holocene CH<sub>4</sub> budget is comprised of natural and anthropogenic emissions. In contrast, the early Holocene was a period when human influence should have been substantially smaller, sodoi:10.5194/cp-2016-75 fatcat:uogfhxwn2vdxtbkscz4npqfgdq
more »... at it allows us to elucidate the natural controls under interglacial conditions. Here we present new high resolution CH<sub>4</sub> records of millennial scale CH<sub>4</sub> variability from Siple Dome, Antarctica, covering from 11.6 to 7.7 thousands of years before 1950&thinsp;AD (ka). We observe several local CH<sub>4</sub> minima on a roughly 1000-year spacing. Each CH<sub>4</sub> minimum corresponds to cool periods in Greenland. We hypothesize that the cooling in Greenland forced the Intertropical Convergence Zone (ITCZ) to migrate southward, reducing rainfall in northern tropical wetlands although there is no obvious change was observed in low latitude hydrology corresponding to abrupt CH<sub>4</sub> reduction at ~&thinsp;10.3&thinsp;ka. A high resolution inter-polar difference (IPD) during the early Holocene increased from ~&thinsp;10.7 to 9.9&thinsp;ka, and remained high until ~&thinsp;9.3&thinsp;ka. With a simple three-box model results, our new IPD records suggest that the ratio of northern high latitude to tropical sources increased due to a boreal source expansion following the deglaciation.
In general, as we stack HTS tapes, such as Bi-2223, transport AC loss increases more than the single tape loss multiplied by the stacked number. That is due to the AC transport current effects of adjacent/neighboring tapes. To find a way to estimate the AC losses of stacked tapes, we fabricated single-, double-and triple-stacked Bi-2223 tapes, which are insulated between the tapes, and measured AC transport current losses in each case. The measured experimental data showed that the AC loss ofdoi:10.1016/s0921-4534(02)01116-4 fatcat:3jx74syjencb7bgsq47ifdtije
more »... acked tapes could be expected using both the loss data of a single tape and the degraded critical current value of stacked tapes.
In this paper, we present GradPIM, a processing-in-memory architecture which accelerates parameter updates of deep neural networks training. As one of processing-in-memory techniques that could be realized in the near future, we propose an incremental, simple architectural design that does not invade the existing memory protocol. Extending DDR4 SDRAM to utilize bank-group parallelism makes our operation designs in processing-in-memory (PIM) module efficient in terms of hardware cost andarXiv:2102.07511v1 fatcat:7iuvb6fdzjdsbio67z6o7qnhb4
more »... nce. Our experimental results show that the proposed architecture can improve the performance of DNN training and greatly reduce memory bandwidth requirement while posing only a minimal amount of overhead to the protocol and DRAM area.
In the conventional wireless power transfer (WPT) using magnetic resonance coupling, power transfer efficiency (PTE) exhibits a peak only at a matched distance between transmitter (Tx) and receiver (Rx). That is, it rapidly degrades if the distance deviates from the matched distance. In order to achieve high PTE over a wide range of the distance, automatic range-adaptation technique is proposed in this work by using multi-loop technique and tunable matching circuit with digital capacitors. Fordoi:10.3390/en11071789 fatcat:cyt2ycsoc5hr5mtvjbpce2rrgu
more »... utomatic range adaptation, the microcontroller unit (MCU) in Rx runs an algorithm to find optimum loop and capacitance for best PTE based on the received power. Tx and Rx are synchronized by using low power Bluetooth wireless communications. Instead of the conventional relays, microelectromechanical system (MEMS) switches with low loss and high isolation are employed to minimize the power dissipation. The entire WPT system automatically maximize PTE with the distance, achieving high PTE of 80.5% at 30 cm and 29.7% at 100 cm. Energies 2018, 11, 1789 12 of 12 itself will be supplied by the proposed WPT system. In this application, Bluetooth BLE plays a great role in wireless data communication between Tx and Rx, as well as for the control of Tx and Rx circuits, for high efficiency wireless power transfer.
This work focuses on the demand response (DR) participation using the energy storage system (ESS). A probabilistic Gaussian mixture model based on market operating results Monte, Carlo Simulation (MCS), is required to respond to an urgent DR signal. However, there is considerable uncertainty in DR forecasting, which occasionally fails to predict DR events. Because this failure is attributable to the intermittency of the DR signals, a non-cooperative game model that is useful for decision-makingdoi:10.3390/en13040883 fatcat:2adjmkhjdvbjpjm7dj5ubday54
more »... on DR participation is proposed. The game is conducted with each player holding a surplus of energy but incomplete information. Consequently, each player can share unused electricity during DR events, engaging in indirect energy trading (IET) under a non-cooperative game framework. The results of the game, the Nash equilibrium (N.E.), are verified using a case study with relevant analytical data from the campus of Gwangju Institute of Science and Technology (GIST) in Korea. The results of the case study show that IET is useful in mitigating the uncertainty of the DR program.
The increase in ambient particulate matter (PM) is affecting not only our daily life but also various industries. To cope with the issue of PM, which has been detrimental to the population of megacities, an advanced demand response (DR) program is established by Korea Power Exchange (KPX) to supplement existing policies in Korea. Ironically, however, DR programs have been launched hurriedly, creating problems for several stakeholders such as local governments, market operators, and DRdoi:10.3390/en13236393 doaj:75bce02a598b4d74a4cd3ef3916b7a02 fatcat:xymvkhcqfjf2lntd7jkyy22vfa
more »... As an alternative, a method for predicting and categorizing the PM through deep learning and fuzzy inference is suggested in this study. The simulation results based on Seoul data show that the proposed model can overcome the problems related to current DR programs and policy loopholes and can provide improvements for some stakeholders. However, the proposed model also has some limitations, which require an in-depth policy consideration or an incentive system for power generation companies.
., 2005; Ryu et al., 2005) (Table 1 and Figure 1 ). ... Other's and we provide evidence supporting the hypothesis that CREB and ERs also target mitochondrial DNA (Yang et al., 2004; Chen et al., 2004a and b; Lee et al, 2005; Ryu et al., 2005) . ... ., 2005; Ryu et al., 2005 NF-κB Cogswell et al., 2003 p53 Marchenko et al., 2000 TFAM (mt-TFA) Parisi et al., 1991 TFB1M Falkenberg et al., 2002 TFB2M Falkenberg et al., 2002 ...doi:10.1002/jnr.21564 pmid:18041090 pmcid:PMC2670446 fatcat:agahtd3ibrambnwd57d2u2lqby
Although steam methane reforming (CH4 + 2H2O → 4H2 + CO2) is the most commercialized process for producing hydrogen from methane, more than 10 kg of carbon dioxide is emitted to produce 1 kg of hydrogen. Methane pyrolysis (CH4 → 2H2 + C) has attracted much attention as an alternative to steam methane reforming because the co-product of hydrogen is solid carbon. In this study, the simultaneous production of hydrogen and separable solid carbon from methane was experimentally achieved in a bubbledoi:10.3390/en14238182 fatcat:at5mv22zx5gbfikknupg2lue24
more »... olumn filled with molten potassium chloride. The melt acted as a carbon-separating agent and as a pyrolytic catalyst, and enabled 40 h of continuous running without catalytic deactivation with an apparent activation energy of 277 kJ/mole. The resultant solid was purified by water washing or acid washing, or heating at high temperature to remove salt residues from the carbon. Heating the solid product at 1200 °C produced the highest purity carbon (97.2 at%). The economic feasibility of methane pyrolysis was evaluated by varying key parameters, that is, melt loss, melt price, and carbon revenue. Given a potassium chloride loss of <0.1 kg of salt per kg of produced carbon, the carbon revenue was calculated to be USD > 0.45 per kg of produced carbon. In this case, methane pyrolysis using molten potassium chloride may be comparable to steam methane reforming with carbon capture storage.
In this study, we report a label-free bone marrow white blood cell classification framework that captures the three-dimensional (3D) refractive index (RI) distributions of individual cells and analyzes with deep learning. Without using labeling or staining processes, 3D RI distributions of individual white blood cells were exploited for accurate profiling of their subtypes. Powered by deep learning, our method used the high-dimensional information of the WBC RI tomogram voxels and achieved highdoi:10.1101/2020.11.13.381244 fatcat:tm6bod2jq5hwhbfvubqkmp4e5u
more »... accuracy. The results show >99 % accuracy for the binary classification of myeloids and lymphoids and >96 % accuracy for the four-type classification of B, T lymphocytes, monocytes, and myelocytes. Furthermore, the feature learning of our approach was visualized via an unsupervised dimension reduction technique. We envision that this framework can be integrated into existing workflows for blood cell investigation, thereby providing cost-effective and rapid diagnosis of hematologic malignancy.
Bovine viral diarrhea virus (BVDV) is prevalent in Korean indigenous cattle, leading to substantial economic losses. This study was conducted to investigate the occurrence of BVDV. In 2016, a total of 143 blood samples were collected from asymptomatic Korean indigenous calves younger than 3-months of age from six different farms in the Republic of Korea (ROK). Results: Eighty-seven calves (60.8%, 87/143) were tested positive for BVDV as evaluated by RT-PCR analysis. Phylogenetic analysis baseddoi:10.1186/s12917-018-1555-4 pmid:30086756 pmcid:PMC6081834 fatcat:nvvwjqet5jhe7gxc7auqahqycy
more »... n the 5′-untranslated region was used to classify these cases into three subtypes: BVDV-1b, BVDV-1o, and BVDV-2a. These results showed that BVDV-1b was the predominant subtype, while 2 samples clustered with BVDV-2a. Interestingly, one sample formed a separate group as a potentially new subtype, BVDV-1o. To our knowledge, this is the first report of BVDV-1o infection in Korean native calves. The BVDV-1o subtype identified in this study was closely related to cattle isolates obtained from Japan, indicating that this subtype is a new introduction to the ROK. Conclusions: This study provides useful information for carrying out epidemiological surveys of BVDV in the ROK and developing a vaccine for future use in the ROK, particularly for the first detection of BVDV-1o in Korean indigenous calves. Further studies are required to investigate the prevalence and pathogenicity of this BVDV-1o subtype.
Objective and Impact Statement. We propose a rapid and accurate blood cell identification method exploiting deep learning and label-free refractive index (RI) tomography. Our computational approach that fully utilizes tomographic information of bone marrow (BM) white blood cell (WBC) enables us to not only classify the blood cells with deep learning but also quantitatively study their morphological and biochemical properties for hematology research. Introduction. Conventional methods fordoi:10.34133/2021/9893804 fatcat:yhyedy7dfnc53mbfuymp7kymvu
more »... ng blood cells, such as blood smear analysis by medical professionals and fluorescence-activated cell sorting, require significant time, costs, and domain knowledge that could affect test results. While label-free imaging techniques that use a specimen's intrinsic contrast (e.g., multiphoton and Raman microscopy) have been used to characterize blood cells, their imaging procedures and instrumentations are relatively time-consuming and complex. Methods. The RI tomograms of the BM WBCs are acquired via Mach-Zehnder interferometer-based tomographic microscope and classified by a 3D convolutional neural network. We test our deep learning classifier for the four types of bone marrow WBC collected from healthy donors (n=10): monocyte, myelocyte, B lymphocyte, and T lymphocyte. The quantitative parameters of WBC are directly obtained from the tomograms. Results. Our results show >99% accuracy for the binary classification of myeloids and lymphoids and >96% accuracy for the four-type classification of B and T lymphocytes, monocyte, and myelocytes. The feature learning capability of our approach is visualized via an unsupervised dimension reduction technique. Conclusion. We envision that the proposed cell classification framework can be easily integrated into existing blood cell investigation workflows, providing cost-effective and rapid diagnosis for hematologic malignancy.
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