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Minwoo Jang,1,* Jong-Hwan Park,1,* Gwon-Min Kim,2 Seunghwan Song,1,3,4 Up Huh,1,3,4 Du-ri Kim,1 Minji Sung,1 Young Jin Tak1,5,6 1Health Convergence Medicine Laboratory, Biomedical Research Institute, Pusan National University Hospital, Busan, 49241, South Korea; 2Department of Medical Research Institute, Pusan National University, Busan, 46241, South Korea; 3Department of Thoracic and Cardiovascular Surgery, Pusan National University School of Medicine, Yangsan, 50612, South Korea; 4Department of Thoracic and Cardiovascular Surgery, Pusan National University Hospital, Busan, 49241, South Korea; 5Department of Family Medicine, Pusan National University School of Medicine, Yangsan, 50612, South Korea; 6Department of Family Medicine, Pusan National University Hospital, Busan, 49241, South Korea*These authors contributed equally to this workCorrespondence: Young Jin Tak, Pusan National University Hospital, 179 Gudeok-Ro, Seo-Gu, Busan, 42941, Republic of Korea, Tel +82 10 7172 5905, Email 03141998@hanmail.netPurpose: Research on whether wearable device interventions can effectively prevent metabolic syndrome remains insufficient. This study aimed to evaluate the effect of feedback on clinical indicators in patients with metabolic syndrome on activities measured using wearable devices, such as smartphone apps.Methods: Patients with metabolic syndrome were recruited and prescribed to live for 12 weeks using a wrist-wearable device (B.BAND, B Life Inc., Korea). A block randomization method was used to distribute participants between the intervention (n=35) and control groups (n=32). In the intervention group, an experienced study coordinator provided feedback on physical activity to individuals through telephonic counseling every other week.Results: The mean number of steps in the control group was 8892.86 (4473.53), and those in the intervention group was 10,129.31 (4224.11). After 12 weeks, metabolic syndrome was resolved. Notably, there were statistically significant differences in the metabolic composition among the participants who completed the intervention. The mean number of metabolic disorder components per person remained at 3 in the control group, and decreased from 4 to 3 in the intervention group. Additionally, waist circumference, systolic and diastolic blood pressure, and triglyceride levels were significantly reduced, while HDL-cholesterol levels were significantly increased in the intervention group.Conclusion: Overall, 12 weeks of telephonic counseling intervention using wearable device-based physical activity confirmation improved the damaged metabolic components of patients with metabolic syndrome. Telephonic intervention can help increase physical activity and reduce waist circumference, which is a typical clinical indicator of metabolic syndrome.Keywords: metabolic syndrome, physical activity, wearable device, waist circumference

Cache side-channel attack is one of the critical security threats to modern computing systems. As a representative cache side-channel attack, Flush+Reload attack allows an attacker to steal confidential information (e.g., private encryption key) by monitoring a victim’s cache access patterns while generating the confidential values. Meanwhile, for providing high performance with memory-intensive applications that do not fit in the on-chip SRAM-based last-level cache (e.g., L3 cache), modern computing systems start to deploy DRAM cache between the SRAM-based last-level cache and the main memory DRAM, which can provide low latency and/or high bandwidth. However, in this work, we propose an approach that exploits the DRAM cache for security rather than performance, called ByCA . ByCA bypasses the L3 shared cache when accessing cache blocks suspected as target blocks of an attacker. Consequently, ByCA eliminates the timing difference when the attacker accesses the target cache blocks, nullifying the Flush+Reload attacks. To this end, ByCA keeps cache blocks suspected as target blocks of the attacker and stores their states (i.e., flushed by clflush or not) in the L4 DRAM cache even with clflush instruction; ByCA re-defines and re-implements clflush instruction not to flush cache blocks from the L4 DRAM cache while flushing the blocks from other level caches (i.e., L1, L2, and L3 caches). In addition, ByCA bypasses L3 cache when the attacker or the victim accesses the target blocks flushed by clflush , making the attacker always obtain the blocks from L4 DRAM cache regardless of the victim’s access patterns. Consequently, ByCA eliminates the timing difference, thus the attacker cannot monitor the victim’s cache access patterns. For L4 DRAM cache, we implement Alloy Cache design and use an unused bit in a tag entry for each block to store its state. ByCA only requires a single bit extension to cache blocks in L1 and L2 private caches, and a tag entry for each block in the L4 DRAM cache. Our experimental results show that ByCA completely eliminates the timing differences when the attacker reloads the target blocks. Furthermore, ByCA does not show the performance degradation for the victim while co-running with the attacker that flushes and reloads target blocks temporally and repetitively.

Purpose The purposes of this study were to examine the influence of a formal sports mentoring program on mentors(pre-service PE teachers), and to identify main factors affecting educational growth of the pre-service teachers. Methods Data were generated in this study using: In-depth interviews, mentoring observations, and document resources from 4 mentors and their mentees as research participants. The collected data were inductively analyzed as an iterative process of working back and forth between the data and the categories(Miles & Huberman, 1994). Results The key findings of this study are as follows. First, mentors developed pre-service teachers’ practical knowledge including teaching knowledge, environment knowledge, student knowledge within teaching contexts. Furthermore, they practiced mentee-centered education through sports mentoring not only by mentees but also for mentees. Second, with respect to the factors impacting mentors’ educational growth, there were two main factors; the systematic structure of a program and mentors’ reflexivity. Mentors improved practical knowledge through the circular ‘experiential learning’ phases the sports mentoring program provided. In addition, mentor had valuable opportunities to learn how to care mentees by reflecting on positive and negative influences deriving from interactions with their mentees. Conclusion Potential benefits were embedded in inherent nature of sport and the unique structure of mentoring. sports mentoring can provide experience of learner-friendly teaching distinct from classes of lecture type. It is necessary to be reconsidered as pre-service PE teacher education program with opportunities of other teaching practice.

Our study examined the association between chronotype, daily physical activity, and the estimated risk of dementia in 170 community-dwelling older adults. Chronotype was assessed with the Horne&ndash, &Ouml, stberg Morningness&ndash, Eveningness Questionnaire (MEQ). Daily physical activity (of over 3 METs) was measured with a tri-axial accelerometer. The Korean version of the Mini-Mental State Examination (K-MMSE) was used to measure the estimated risk of dementia. The evening chronotype, low daily physical activity, and dementia were positively associated with each other. The participants with low physical activity alongside evening preference had 3.05 to 3.67 times higher estimated risk of developing dementia, and participants with low physical activity and morning preference had 1.95 to 2.26 times higher estimated risk than those with high physical activity and morning preference. Our study design does not infer causation. Nevertheless, our findings suggest that chronotype and daily physical activity are predictors of the risk of having dementia in older adults aged 70 years and above.

This study aimed to investigate the association between a virtual reality (VR) intervention program and cognitive, brain and physical functions in high-risk older adults. In a randomized controlled trial, we enrolled 68 individuals with mild cognitive impairment (MCI). The MCI diagnosis was based on medical evaluations through a clinical interview conducted by a dementia specialist. Cognitive assessments were performed by neuropsychologists according to standardized methods, including the Mini-Mental State Examination (MMSE) and frontal cognitive function: trail making test (TMT) A & B, and symbol digit substitute test (SDST). Resting state electroencephalogram (EEG) was measured in eyes open and eyes closed conditions for 5 minutes each, with a 19-channel wireless EEG device. The VR intervention program (3 times/week, 100 min each session) comprised four types of VR game-based content to improve the attention, memory and processing speed. Analysis of the subjects for group–time interactions revealed that the intervention group exhibited a significantly improved executive function and brain function at the resting state. Additionally, gait speed and mobility were also significantly improved between and after the follow-up. The VR-based training program improved cognitive and physical function in patients with MCI relative to controls. Encouraging patients to perform VR and game-based training may be beneficial to prevent cognitive decline.

In this article, we empirically investigate the impact of the population age structure on electricity demand. Our study is motivated by suggestions from existing literature that demographic factors can play an important role in energy demand. Using Korean regional level panel data for 2000 to 2016, we estimate the long-run elasticities through employing cointegration regression and the short-run marginal effects by developing a panel error correction model. It is worth investigating the Korean case, since Korea is aging faster than any other advanced economy, and at the same time is one of the heaviest energy users in the world. To our knowledge, this is the first study analyzing how the population age structure affects residential electricity demand, based on regional data in Korea. Our analysis presents the following results. First, an increase in the youth population raises the residential electricity demand in the short- and long-run. Second, an increase in the population of people aged 65 and over also increases this electricity demand in the short- and long-run. Third, among the group of people aged 65 and over, we further investigate the impact of an older population group, aged 80 and over, but separately, on their residential electricity demand. However, in general there is no strong relationship in the short- and long-run.

Mounting evidence shows that economic and climate variables such as income, energy price, and temperature impact energy demand. We examined another variable, population age distribution, which has rarely been considered, that could affect energy demand. We employ population polynomials to account for the impact of population age distribution on residential electricity consumption in Korea. Using panel data from 1990 to 2016, we verify that populations aged 20~44, and those over 60, raise residential electricity consumption. We additionally evaluate the impact of population age distribution in forecasting future electricity consumption and conclude that age distribution effects dominate total population growth effects.

Recently, a key-value store has been used to improve the throughput and latency performance in distributed computing environments. However, some or all of the data must be processed in the memory to guarantee the performance if the data workload increases greatly. However, there is a bottleneck because of the data replication overheads incurred by the memory to guarantee availability. In this study, we implemented and evaluated the delayed replication of data in the memory to reduce the overheads of the key-value store, which stores and manages data in the memory. The results of the experiments showed that the performance was improved by 11% after applying delayed replication.

Software birthmarks are unique and native characteristics of a binary executable program that can be used for detecting software piracy. API (Application Programming Interface) calls in an MS Windows binary executable can be used as software birthmarks when there are no source codes available to detect software similarity. However, it is inefficient to extract birthmarks from all API calls during the execution of a binary executable. In this paper, we propose an efficient scheme for comparing software similarity. To reduce the number of comparisons used in the proposed scheme, we extract only the core API calls that are explicitly used in different programs. The birthmarks used for comparing the similarity between two programs can be obtained by extracting these core API calls. Our experimental results show that this proposed birthmark scheme using core API calls is efficient for evaluating software similarity.

Flash file systems that are not cleanly unmounted (e.g., in the event of power failure or an abnormal shutdown) may cause a scan of all flash memory when the system is remounted in order to gather all inode information and store it in RAM. This results in an unacceptably long flash file system mounting time depending mainly on the size. This long reconstruction delay makes the flash file systems unsuitable for embedded systems which require high availability. In this paper, we propose a fast mount mechanism for flash file systems which relies on a block inband tag with the chunk deletion history. This provides the ability to selectively scan the tag of the blocks at the mount time. The proposed scheme is implemented in YAFFS2 (Yet Another Flash File System 2). The evaluation results show that our scheme reduces the mounting time by as much as 40% compared to an existing scheme. This method can be used with an embedded system application that requires higher level of availability, such as a surveillance system.