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Aims: Homeostasis model assessment for insulin resistance (HOMA-IR) is a biomarker for Type 2 diabetes mellitus(T2DM). However, the role of HOMA-IR in the non-diabetic is unclear. Methods: From a prospective community-based cohort of 10,030 individuals, 4,314 individuals younger than 65 years and without diabetes were enrolled and divided into three groups by baseline HOMA-IR tertiles: high (n=1244), moderate (n=1248), and low (n=1822). The primary outcome was new onset T2DM. Secondary outcomes were chronic kidney disease (CKD) and a composite of coronary artery disease, myocardial infarction, and stroke as macrovascular events. Results:The mean age was 51 years. The prevalence of hypertension and cholesterol and HbA1c were higher in the high HOMA-IR group. New onset T2DM (6.3%) and CKD (12.2%) incidence in the high HOMA-IR group was higher than in the others. The prevalence of macrovascular events did not differ among groups. High-HOMA-IR was an independent risk factor for new onset T2DM (odds ratio 2.07 [1.32-3.25]; p =0.001) and CKD (1.42 [1.08-1.87]; p =0.01). Conclusions:High HOMA-IR was an early predictor of new onset T2DM and CKD regardless of the HbA1c in non-diabetic individuals. Further research on the specific cut off value will be needed.

Due to the prolonged COVID-19 pandemic and various restrictions, peoples’ leisure activity patterns significantly change. Thus, it is necessary to understand how people’s travel and leisure behaviors have changed during the COVID-19 pandemic. However, there is still a lack of empirical evidence on how individuals’ COVID-19 risk perception influences their leisure destination choice behavior. This empirical study aims to confirm the relationship between risk perception of COVID-19 and choice of leisure destination and to explore any differences between them related to demographic characteristics. A total of 537 valid samples were used for SUR model analysis by conducting an online survey targeting citizens of the Seoul metropolitan area, Korea. Our findings show that the risk perception of COVID-19 has a significant effect on the choice of leisure places. In particular, the risk perception of COVID-19 has a positive effect on the choice of natural places, disinfected areas, and socially distanced spaces while negatively influencing the choice of crowded leisure places. In addition, age and gender are more effective factors than other control variables in COVID-19 risk perception and leisure destination choices. Furthermore, this study also provides several implications for urban leisure place planners and service providers to respond to the changing leisure activity patterns caused by COVID-19.

In cloud computing, there is a trade-off between SLAV (Service Level Agreement Violation) and system operating cost. Violation rates can be decreased when using more hosts, which increases system operating costs. Therefore, to manage the resources of those hosts efficiently, finding an optimal balancing point between SLAV and system operating cost is critical. In addition, a cost-effective load balancing approach based on the proper migration of VMs (Virtual Machines) in the hosts is needed. For this purpose, some indicators are also necessary to identify the abnormal hosts that violate SLA. One of the primary indicators, CPU usage, is closely related to energy consumption and can be used to reduce SLAV and energy consumption effectively. Our approach focuses on the special environment such as the cloud environment for the scientific data. Here, most of the jobs are data-intensive and a large amount of disk operations is required. Owing to disk operations are likely to affect the performance degradation of the host, disk bandwidth usage as well as CPU usage should be also considered. In this study, we propose the Min-Max Exclusive VM Placement (MMEVMP) strategy to minimize both SLAV and energy consumption. The current working system called KIAF (KISTI Analysis Facility), the CERN ALICE experimental cloud environment for scientific data analysis, is used to analyze the characteristics of data-intensive jobs within it. In this experiment, a lightweight version of the CloudSim simulator was developed and the results were compared to the other methods of different policies. Our evaluation showed that our proposed strategy can reduce SLA violation reasonably as well as the system operating cost-effectively.

The 24Mg(p,α)21 Na transfer reaction has been previously studied for a spectroscopic study of 21Na [Cha et al., Phys. Rev. C 96, 025810 (2017)]. In this follow-up analysis, the proton decays of the excited states of the radionuclide 21Na, which were measured simultaneously, are reported. By investigating the coincidence between the reaction α-particles and decay protons, we were able to identify three groups of events that are associated with the energy levels in 20Ne. The 20Ne excitation energy plot was obtained as a result. The four lowest known energy levels in 20Ne (the ground state and excited states at Ex = 1.633, 4.247 and 4.966 MeV) were clearly observed.

BackgroundPatients with cardiovascular disease (CVD) tend to have higher mortality rates and reduced physical activity (PA). We aimed to evaluate the effect of PA on mortality in older adults with specific CVD.MethodsWe enrolled 68,223 participants (n = 23,871 with CVD, n = 44,352 without CVD) aged ≥65 years with available physical activity data between 2005 and 2012 from the Korean National Health Insurance Service of Korea-Senior database. CVD was defined as a history of ischemic stroke, transient ischemic attack, heart failure, myocardial infarction, and peripheral artery disease.ResultsPatients with CVD were older than those without CVD. Compared with the sedentary group, the physically active groups with and without CVD had a lower incidence and risk of all-cause death during a median follow up period of 42 (interquartile range 30–51) months. A 500 metabolic equivalent task-min/week increase in PA resulted in an 11% and 16% reduction in the risk of mortality in the non-CVD and CVD groups, respectively. With regard to specific CVDs, the risk of mortality progressively reduced with increasing PA in patients with heart failure or myocardial infarction. However, the reduction reached a plateau in patients with stroke or peripheral artery disease, but was significantly greater in patients with stroke (20% vs. without stoke, 11%, Pint = 0.006) or heart failure (13% vs. without heart failure, 11%; Pint = 0.045)ConclusionsPA was associated with a reduced risk of all-cause mortality in older adults with and without CVD. The benefits of PA in patients with CVD, especially patients with stroke or heart failure, were greater than those without.

Data are important and ever growing in data-intensive scientific environments. Such research data growth requires data storage systems that play pivotal roles in data management and analysis for scientific discoveries. Redundant Array of Independent Disks (RAID), a well-known storage technology combining multiple disks into a single large logical volume, has been widely used for the purpose of data redundancy and performance improvement. However, this requires RAID-capable hardware or software to build up a RAID-enabled disk array. In addition, it is difficult to scale up the RAID-based storage. In order to mitigate such a problem, many distributed file systems have been developed and are being actively used in various environments, especially in data-intensive computing facilities, where a tremendous amount of data have to be handled. In this study, we investigated and benchmarked various distributed file systems, such as Ceph, GlusterFS, Lustre and EOS for data-intensive environments. In our experiment, we configured the distributed file systems under a Reliable Array of Independent Nodes (RAIN) structure and a Filesystem in Userspace (FUSE) environment. Our results identify the characteristics of each file system that affect the read and write performance depending on the features of data, which have to be considered in data-intensive computing environments.

To investigate the propagation of meteorological droughts to agricultural and hydrological droughts, the relationship between droughts was analyzed using observed precipitation and agricultural reservoir and dam storage levels with SPI from 1998 to 2015 in South Korea. For the relationship between different types of droughts, we find that the occurrence of meteorological droughts after concentrated precipitation in the wet season (from June to September) tends not to lead to agricultural or hydrological droughts. A lack of precipitation from April to September, when large volumes of irrigation water are consumed, triggers both meteorological and agricultural droughts. In the case of hydrological droughts propagated from meteorological droughts, precipitation deficits in the dry season (between October and March) caused decrease in dam storage levels only. The occurrence of all different types of droughts is associated with extreme meteorological droughts, which are mainly caused by precipitation deficits in the wet season or prolonged rainfall shortages; in these cases, meteorological droughts led to agricultural and hydrological droughts. An analysis of the seasonal characteristics of storage level changes that in the wet season, agricultural reservoir storage levels are more dependent on precipitation deficits than dam storage levels. On other hand, when precipitation deficits were recorded in the dry season, agricultural reservoir storage levels went up, but dam storage levels dropped. The propagation of meteorological droughts to agricultural and hydrological droughts depends not only on drought severity but also on the drought timing. These findings may contribute to establishing a comprehensive drought monitoring system.

The $^{7}\mathrm{Li}(\ensuremath{\gamma},t)^{4}\mathrm{He}$ ground state cross section was measured for the first time using monoenergetic $\ensuremath{\gamma}$ rays with energies between 4.4 and 10 MeV at the High Intensity Gamma-ray Source. The reaction is important for the primordial Li problem and for testing our understanding of the mirror $\ensuremath{\alpha}$-capture reactions $^{3}\mathrm{H}(\ensuremath{\alpha},\ensuremath{\gamma})^{7}\mathrm{Li}$ and $^{3}\mathrm{He}(\ensuremath{\alpha},\ensuremath{\gamma})^{7}\mathrm{Be}$. Although over the last 30 years most measurements of the $^{3}\mathrm{H}(\ensuremath{\alpha},\ensuremath{\gamma})^{7}\mathrm{Li}$ reaction have concentrated in an energy range below ${E}_{\ensuremath{\gamma}}=3.65$ MeV, measurements at higher energies could potentially restrict the extrapolation to astrophysically important energies. The experimental arrangement for measuring the $^{7}\mathrm{Li}(\ensuremath{\gamma},t)^{4}\mathrm{He}$ reaction included a large-area silicon detector array and several beam characterization instruments. The experimental astrophysical $S$ factor of $^{3}\mathrm{H}(\ensuremath{\alpha},\ensuremath{\gamma})$ calculated from the present data was fitted using the $R$-matrix formalism. The results are in disagreement with previous experimental measurements in the same energy range but the extrapolated $S$ factor agrees with the potential model calculation and lower energy experimental data.

The α-clusterization of an atomic nucleus has been studied for a long time, even from the earliest days of nuclear physics. Our understanding of the α-cluster structure is, however, mainly limited to the self-conjugate A = 4n (n = 2, 3, 4, · · · ) light nuclei and some of the neutron-rich radionuclides such as 10Be, 11B, and 14C. In order to study the α-cluster structure of a neutron-deficient 22Mg nucleus, we have measured the 18Ne(α, α)18Ne scattering in inverse kinematics by using radioactive 18Ne beams and the 4He gas target at the Center for Nuclear Study radioactive ion beam separator of the University of Tokyo. Recoiling α particles from the scattering were detected by using silicon strip detectors, which constitute ΔE-E telescopes for particle identification. By adopting a thick target method, we were able to investigate a wide range of excitation energies Ex = 9.9 - 16.5 MeV in 22Mg in this work.

A gas-filled ionization chamber is well suited for low energy nuclear physics applications such as measuring beam intensities and detecting heavy recoils from nuclear reactions. Recently developed multi-electrode ionization chamber shows great performance in terms of the energy resolution and the maximum counting rate. It requires, however, iterative energy loss calculations for certain applications mainly due to its complex geometry. For easier energy loss calculations, a stopping power calculation code called the Multi-electrode Ionization Chamber Energy Loss Calculator (MICE) has been developed by utilizing the Java programming language. The development procedure, usage, and application of the MICE are reported.

Compton γ -ray sources have been in operation for over 30 years with new facilities being under construction or proposed. The gamma beam system under implementation at the Extreme Light Infrastructure - Nuclear Physics facility in Romania will deliver brilliant γ -ray beams with energies up to 19.5 MeV. Several instruments for measuring the parameters of the γ -ray beam are under development at ELI-NP. One of these instruments based on a High Purity Germanium detector is routinely used for beam energy measurements at other facilities. Here we investigate the use of a High Purity Germanium detector to continuously monitor the intensity of the ELI-NP gamma beam by measuring the inelastic scattering of photons. This method relies on both experimental and simulated data and it has been successfully tested during a recent experiment at the High Intensity γ -ray Source facility.

Mini-solar photovoltaics, which are installed on apartment balconies, are rapidly spreading in Seoul, South Korea. Seoul has implemented a policy to diffuse mini-solar photovoltaics in apartments for energy transition since 2012. The policy considers compact land use and a large population of the city. This study examines a variety of variables in relation to the adoption of mini-solar photovoltaics. In particular, we focus on peer effects, namely, those of spatially adjacent, previously installed mini-solar photovoltaics. As apartment characteristics, four variables are selected to assess both within and between apartment complexes: one for the density of adopters as a within-complex variable and three for the number of adopters in the 500 m, 1 km, and 1.5 km radius of apartment complexes as between-complex variables. A major finding is that peer effects significantly contribute to the new adoption of mini-solar photovoltaics. Implications of this finding are discussed in an urban context.

A position-sensitive ionization chamber has been constructed and commissioned at the Physics Department of Sungkyunkwan University to extract position information on incident charged particles for future nuclear reaction measurements. By utilizing the newly-designed position-sensitive anodes and the previously-commissioned portable gas-filled ionization chamber by Chae et al., position information on incident particles could be obtained. The device was tested with an 241Am α-emitting source, and the standard deviation of the fitted Gaussian distribution was measured to be 1.76 mm when a collimator with a 2 mm hole was used.

The public housing needs maintenance administration for improvement and retainment of residential condition by means of tenants participation. However, most researchers have considered tenants as passive participants in this context. The previous studies did not comprehend perspective of tenants participation and just measured the management preference and the level of satisfaction on maintenance. This study investigates the attitudes and perceptions of tenants on participation in public housing maintenance by introduced Q method that provides a systematic and rigorous quantitative means for examining human subjectivity. The subjectivity is classified as types according to cost and benefit factors by principal components analysis and varimax rotation of the extracted factors. As a result, this study present 5 types of tenants participation and expect to discuss desirable roles of tenant and org anization in public housing maintenance.

We performed an experiment to measure proton resonant elastic scattering of a mixed 26m,gAl beam with a thick target in inverse kinematics by using CNS RI beam sep-arator, located at RIKEN Nishina Center. It aimed to search for strong proton resonances and determine level properties of low spin-parity states in 27Si. Diagnosis of the 26mAl purity of the beam by annihilation radiation are discussed.

Activity recognition is the core technology of intelligent video surveillance systems and focuses on the behavior of a single object or a pair of objects. A common approach to activity recognition is to first extract and track the characteristics of moving objects from an image sequence, with the goal of converting pixel-level data into low-level functions appropriate for activity analysis. And in these methods, it is important to successfully extract good features and analyze the spatio-temporal interaction of the type of object moving from the extracted features. In this paper, we propose a three step activity recognition model that takes into account the spatial elements of the trajectory using time series data of moving pedestrian trajectories. Activity recognition modeling used the c4.5 algorithm and performed recognition experiments on the four behaviors defined in the CAVIAR dataset.

Detection-based pedestrian counting methods produce results of considerable accuracy in non-crowded scenes. However, the detection-based approach is dependent on the camera viewpoint. On the other hand, map-based pedestrian counting methods are performed by measuring features that do not require separate detection of each pedestrian in the scene. Thus, these methods are more effective especially in high crowd density. In this paper, we propose a hybrid map-based model that is a new directional pedestrian counting model. Our proposed model is composed of direction estimation module with classified foreground motion vectors, and pedestrian counting module with principal component analysis. Our contributions in this paper have two aspects. First, we present a directional moving pedestrian counting system that does not depend on object detection or tracking. Second, the number and major directions of pedestrian movements can be detected, by classifying foreground motion vectors. This representation is more powerful than simple features in terms of handling noise, and can count the moving pedestrians in images more accurately.

The advent of radioactive ground-state beams some three decades ago ultimately sparked a revolution in our understanding of nuclear physics. However, studies with radioactive isomer beams are sparse and have often required sophisticated apparatuses coupled with the technologies of ground-state beams due to typical mass differences on the order of hundreds of keV and vastly different lifetimes for isomers. We present an application of a isomeric beam of 26m Al to one of the most famous observables in nuclear astrophysics: galactic 26 Al. The characteristic decay of 26 Al in the Galaxy was the first such specific radioactivity to be observed originating from outside the Earth some four decades ago. We present a newly-developed, novel technique to probe the structure of low-spin states in 27 Si. Using the Center for Nuclear Study low-energy radioisotope beam separator (CRIB), we report on the measurement of 26m Al proton resonant elastic scattering conducted with a thick target in inverse kinematics. The preliminary results of this on-going study are presented.

In this paper, we propose an intelligent situation recognition model by collecting and analyzing multiple sensor signals. Multiple sensor signals are collected for fixed time window. A training set of collected sensor data for each situation is provided to K2-learning algorithm to generate Bayesian networks representing causal relationship between sensors for the situation. Statistical characteristics of sensor values and topological characteristics of generated graphs are learned for each situation. A neural network is designed to classify the current situation based on the extracted features from collected multiple sensor values. The proposed method is implemented and tested with UCI machine learning repository data.

Since it costs a lot to build a home network system of new service provider, the entry barrier is quite high. If it would be possible to build a home network system with high performance at a low building cost, it would be quite attractive. If a home network would be built in P2P-SIP(Peer to peer - Session Initiation Protocol) structure, it is possible to decrease server maintenance cost and keep high usability by deconcentrating the traffic concentrated on the server. It is also possible to efficiently manage the location information of terminal, if quorum system based on fuzzy logic would be applied. In this paper we propose the P2P-SIP structure applied of quorum system based on fuzzy logic by which a home network system can be built at low cost. It was possible to know by comparing the structure with existing one that the structure has very good performance.

The KHIMA (Korea Heavy Ion Medical Accelerator) had developed the KIRAMS-30 cyclotron in collaboration with the ARTI (Advanced Radiation Technology Institute). This cyclotron is able to accelerate proton for the mass production of radioisotopes. It is designed to use two normal conduct RF cavities. The resonant frequency of the ion is 15.99 MHz because of the magnet design and the beam dynamics. The RF frequency is 63.96 MHz because of the 4th harmonic number. By using computer simulation codes, we estimated the principle design parameters of the RF system, we simulated the electric field distribution. In this paper, we present the design features, the results of quality assessment tests for the RF system, and important issues taken into consideration when designing such a cyclotron.

Motion correspondence problem between many feature points of consecutive frames is computationally explosive. We present a heuristic algorithm for finding out the most probable motion correspondence of points in consecutive frames, based on fuzzy confidence degrees. The proposed algorithm consists of three stages: (i) reduction of the search space for candidate points of association, (ii) pairwise association cost estimation and (iii) complete association of every feature point between the consecutive frames. In the first stage, all the points in a frame, frame t-1 are grouped into several groups by using fuzzy clustering. This is done with a Euclidean distance as a similarity measure between the points. The points in the following frame, frame t are also clustered into the same number of groups with respect to the cluster centers of the previous frame. The association between the points of the consecutive frames is allowed only for the points that belong to the same group in each frame. In the second stage, the cost of each association of a point in frame t-1 with a point in frame t is estimated by using motion constraints that are based on the velocity vector and the orientation angle of each point. The cost is measured as a fuzzy confidence degree of each head point, i.e., a point in frame t-1, belonging to each measurement, i.e., a point in frame t. In the final stage, we search for the most likely associations among all the possible mappings between the feature points in the consecutive frames. A search tree is constructed in such a way that an ith level node represents an association of ith node in frame t-1 with a node in frame t. We devise a heuristic function of an admissible A* algorithm by using the pairwise association cost developed in the second stage. Experimental results show an accuracy of more than 98%.

A video analysis system used to detect events in video streams generally has several processes, including object detection, object trajectories analysis, and recognition of the trajectories by comparison with an a priori trained model. However, these processes do not work well in a complex environment that has many occlusions, mirror effects, and/or shadow effects. We propose a new approach to a context-aware video surveillance system to detect predefined contexts in video streams. The proposed system consists of two modules: a feature extractor and a context recognizer. The feature extractor calculates the moving energy that represents the amount of moving objects in a video stream and the stationary energy that represents the amount of still objects in a video stream. We represent situations and events as motion changes and stationary energy in video streams. The context recognizer determines whether predefined contexts are included in video streams using the extracted moving and stationary energies from a feature extractor. To train each context model and recognize predefined contexts in video streams, we propose and use a new ensemble classifier based on the AdaBoost algorithm, DAdaBoost, which is one of the most famous ensemble classifier algorithms. Our proposed approach is expected to be a robust method in more complex environments that have a mirror effect and/or a shadow effect.

We present an analysis of a simulated climate projection covering the period 1971-2080 over the Korean Peninsula with a regional climate model (RegCM3) using a one-way double-nested system. The mother and nested domain cover the East Asian region at 60 km grid spacing and the Korean Peninsula at 20 km grid spacing, respectively. The mean climate state as well as the frequency and intensity of daily extreme events are investigated at various temporal and spatial scales, with a focus on surface air temperature and precipitation. Our analysis is primarily centered on the comparison of two 30-year climate periods between 2021-2050 and 2051-2080, in order to assess climatic changes at different time periods in response to anthropogenic forcings under the IPCC B2 emission scenario. Regarding the interdecadal variation of projected temperature and precipitation over the whole integration period, we find that the temperature change gradually increases by 3.2 K for the 2070s, with a persistently increasing trend. The projected precipitation in the future shows generally greater amounts than in the reference run despite significant interdecadal variation. A substantial increase (decrease) of hot (frost) spells is projected along with increasing of maximum and minimum temperature. Wet spells of long periods tend to be more frequent, accompanying the increase of precipitation amounts. The temperature changes are statistically significant at the 90% confidence level in all seasons and regions, indicating robustness of the projected change while the precipitation changes show low statistical confidence, especially summer season, due to the large natural variability. Based on the spatial distribution, although the general pattern between the mother and nested domain simulations shows similarity, more detailed structure over Korea is found in the nested domain simulation. By comparison of the change between 2021-2050 and 2051-2080 periods, the climate change signal of both temperature and precipitation becomes more pronounced in the late 21 st century as the greenhouse gas concentration is increased.