• Wind and Structures
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• v.32 no.4
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• pp.355-369
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• 2021

Shape optimization of tall buildings is an efficient approach to mitigate wind-induced effects. Several studies have demonstrated the potential of shape modifications to improve the building's aerodynamic properties. On the other hand, it is well-known that the cross-section geometry has a direct impact in the floor area availability and subsequently in the building's profitability. Hence, it is of interest for the designers to find the balance between these two design criteria that may require contradictory design strategies. This study proposes a surrogate-based multi-objective optimization framework to tackle this design problem. Closed-form equations provided by the Eurocode are used to obtain the wind-induced responses for several wind directions, seeking to develop an industry-oriented approach. CFD-based surrogates emulate the aerodynamic response of the building cross-section, using as input parameters the cross-section geometry and the wind angle of attack. The definition of the building's modified plan shapes is done adopting the reduced basis approach, advancing the current strategies currently adopted in aerodynamic optimization of civil engineering structures. The multi-objective optimization problem is solved with both the classical weighted Sum Method and the Weighted Min-Max approach, which enables obtaining the complete Pareto front in both convex and non-convex regions. Two application examples are presented in this study to demonstrate the feasibility of the proposed strategy, which permits the identification of Pareto optima from which the designer can choose the most adequate design balancing profitability and occupant comfort.

• Journal of Climate Change Research
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• v.2 no.3
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• pp.191-201
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• 2011

This study investigates how green infrastructure, including natural and open space such as forests, rivers, parks, and streets, could effectively counteract climate change in terms of mitigation and adaption, respectively. As a result, green infrastructure, such as forests, parks, vegetable gardens, roof gardens, pedestrian walkways, bike lanes, etc, could effectively mitigate climate change: 1) Carbon storage and sequestration; 2) Fossil fuel substitution; 3) Material substitution; 4) Food production 5) Reducing the need to travel by car. Secondly, green infrastructure, such as rivers, tree-lined streets, farmland, wetlands, dunes, wind ways, etc, could adapt to climate change: 1) Managing high temperatures; 2) Managing water supply; 3) Managing ravine flooding; 4) Managing costal flooding; 5) Managing surface water; 6) Reducing soil erosion; 7) Helping other species to adapt.

• 한국사회정책
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• v.25 no.2
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• pp.31-55
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• 2018

The economic penalty of care and gender inequality reinforce each other. Unequal distribution and treatment of care are at the basis of gender inequality. Care creates economic penalty that deepen gender inequality. Those who perform care work tend to take the position of the vulnerable in socio-economic power relations. Due to their weak position, it is difficult for them to voice out a fair treatment and reward for their work. As a result, care workers both at home and in the public sector suffering from lower economic value of care are positioned in unequal gender relations with more vulnerable socioeconomic status. The basic income system may have the potential to mitigate multifaceted gender inequalities in our society. For the introduction of basic income to help realize the real freedom for women, it is necessary to understand unique natures of care work and tackle economic penalties of care work. This paper examines the relationships between care penalties and basic income, focusing on the debate on the introduction of the basic income system. We argue that if the economic penalties caused by unique natures of care work are not eased or resolved, the introduction of the basic income may not contributes to alleviating gender inequalities.

• Journal of the Korean Geosynthetics Society
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• v.17 no.4
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• pp.157-168
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• 2018

Recently, the occurrence of typhoons and heavy rainfall is increasing due to climate change. This causes increase in possibility of landslide damages in rural areas. However, in reality, the precise engineering stability assessment studies are still insufficient. Therefore, in order to reduce the landslide damages and effectively manage mountainous areas, the development of disaster prevention techniques is needed. In this study, to analyze the shock absorbing effect of the buffer-spring during application of dynamic impact load in the debris flow protection system, numerical analysis is carried out for each free field of the buffer-spring and the load sharing ratio of the buffer-spring is also examined. In addition, the field applicability is verified by comparison of the tensile strength of the conventional buffer-spring and the wedge type buffer-spring on various magnitudes of dynamic impact load. As a result of the study, it is found that the net-type debris protection system is effective to mitigate loss of properties and human lifes during landslide.

• Earthquakes and Structures
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• v.16 no.3
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• pp.349-358
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• 2019

Long span cable-stayed bridges are extremely vulnerable to dynamic excitations such as which caused by traffic load, wind and earthquake. Studies on cable-stayed bridge vibration control have been keenly interested by researchers and engineers in design new bridges and assessing in-service bridges. In this paper, a novel Hybrid-Tuned Mass Damper (H-TMD) is proposed and a hybrid control model named Mixed Logic Dynamic (MLD) is employed to build the bridge-H-TMD system to mitigate the vibrations. Firstly, the fundamental theory and modeling process of MLD model is introduced. After that, a new state switching design of the H-TMD and state space equations for different states are proposed to control the bridge vibrations. As the state switching designation presented, the H-TMDs can applied active force to bridge only if the structural responses are beyond the limited thresholds, otherwise, the vibrations can be reduced by passive components of dampers without active control forces provided. A new MLD model including both passive and active control states is built based on the MLD model theory and the state switching design of H-TMD. Then, the case study is presented to demonstrate the proposed methodology. In the case study, the control scheme with H-TMDs is applied for a long span cable-stayed bridge, and the MLD model is established and simulated with earthquake excitation. The simulation results reveal that the suggested method has a well damping effect and the established system can be switched between different control states as design excellently. Finally, the energy consumptions of H-TMD schemes are compared with that of Active Tuned Mass Damper (ATMD) schemes under variable seismic wave excitations. The compared results show that the proposed H-TMD can save energy than ATMD.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.205-214
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• 2019

Android uses app cache files to improve app execution performance. However, this optimization technique may raise security issues that need to be examined. In this paper, we present a practical design of "Android app cache manipulation attack" to intentionally modify the cache files of a target app, which can be misused for stealing personal information and performing malicious activities on target apps. Even though the Android framework uses a checksum-based integrity check to protect app cache files, we found that attackers can effectively bypass such checks via the modification of checksum of the target cache files. To demonstrate the feasibility of our attack design, we implemented an attack tool, and performed experiments with real-world Android apps. The experiment results show that 25 apps (86.2%) out of 29 are vulnerable to our attacks. To mitigate app cache manipulation attacks, we suggest two possible defense mechanisms: (1) checking the integrity of app cache files; and (2) applying anti-decompilation techniques.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.71-79
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• 2019

By using convolutional neural networks (CNNs) based on semantic segmentation, road surface damage detection has being studied. In order to generate the CNN model, it is essential to collect the input and the corresponding labeled images. Unfortunately, such collecting pairs of the dataset requires a great deal of time and costs. In this paper, we proposed a road surface damage detection technique based on semi-supervised learning using pseudo labels to mitigate such problem. The model is updated by properly mixing labeled and unlabeled datasets, and compares the performance against existing model using only labeled dataset. As a subjective result, it was confirmed that the recall was slightly degraded, but the precision was considerably improved. In addition, the $F_1-score$ was also evaluated as a high value.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.739-751
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• 2019

Security in embedded devices has become a significant issue. Threats on the sup-ply chain, like using counterfeit components or inserting backdoors intentionally are one of the most significant issues in embedded devices security. To mitigate these threats, high-level security evaluation and certification more than EAL (Evaluation Assurance Level) 5 on CC (Common Criteria) are necessary on hardware components, especially on the cryptographic module such as AES. High-level security evaluation and certification require detecting covert channel such as backdoors on the cryptographic module. However, previous studies have a limitation that they cannot detect some kinds of backdoors which leak the in-formation recovering a secret key on the cryptographic module. In this paper, we present an expanded definition of backdoor on hardware AES module and show how to detect the backdoor which is never detected in Verilog HDL using model checker NuSMV.

• Nutrition Research and Practice
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• v.13 no.4
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• pp.286-294
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• 2019

BACKGROUND/OBJECTIVES: Docosahexaenoic acid (DHA), an n-3 long chain polyunsaturated fatty acid (LCPUFA), is acquired by dietary intake or the in vivo conversion of ${\alpha}$-linolenic acid. Many enzymes participating in LCPUFA synthesis are regulated by peroxisome proliferator-activated receptor alpha ($PPAR{\alpha}$). Therefore, it was hypothesized that the tissue accretion of endogenously synthesized DHA could be modified by $PPAR{\alpha}$. MATERIALS/METHODS: The tissue DHA concentrations and mRNA levels of genes participating in DHA biosynthesis were compared among $PPAR{\alpha}$ homozygous (KO), heterozygous (HZ), and wild type (WT) mice (Exp I), and between WT mice treated with clofibrate ($PPAR{\alpha}$ agonist) or those not treated (Exp II). In ExpII, the expression levels of the proteins associated with DHA function in the brain cortex and retina were also measured. An n3-PUFA depleted/replenished regimen was applied to mitigate the confounding effects of maternal DHA. RESULTS: $PPAR{\alpha}$ ablation reduced the hepatic Acox, Fads1, and Fads2 mRNA levels, as well as the DHA concentration in the liver, but not in the brain cortex. In contrast, $PPAR{\alpha}$ activation increased hepatic Acox, Fads1, Fads2, and Elovl5 mRNA levels, but reduced the DHA concentrations in the liver, retina, and phospholipid of brain cortex, and decreased mRNA and protein levels of the brain-derived neurotrophic factor in brain cortex. CONCLUSIONS: LCPUFA enzyme expression was altered by $PPAR{\alpha}$. Either $PPAR{\alpha}$ deficiency or activation-decreased tissue DHA concentration is a stimulus for further studies to determine the functional significance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.8
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• pp.566-573
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• 2019

In order to obtain high-quality images by motion compensation in the airborne synthetic aperture radar (SAR), accurate motion sensing in image acquisition section is necessary. Especially, reducing relative position error and discontinuity in motion sensing is important. To overcome the problem, we propose a pre-parametric error modeling (P-PEM) algorithm which is a real-time motion sensing algorithm for the airborne SAR in this paper. P-PEM is an extended version of parametric error modeling (PEM) method which is a motion sensing algorithm to mitigate the errors in the previous work. PEM estimates polynomial coefficients of INS error which can be assumed as a polynomial in the short term. Otherwise, P-PEM estimates polynomial coefficients in advance and uses at image acquisition section. Simulation results show that the P-PEM reduces relative position error and discontinuity effectively in real-time.