Watch Out! Smartwatches as criminal tool and digital forensic investigations

In the rapidly advancing technological landscape, smartwatches have materialized as multifunctional devices integral to our daily routines. Smartwatches store a substantial amount of personal information, potentially serving as repositories of digital evidence. Thus, digital forensic researchers have devoted considerable effort to exploring smartwatch forensic techniques. However, it has been observed that prior studies have primarily treated smartwatches as mere storage mediums for digital evidence, neglecting their potential role in criminal activities. This paper presents the information leakage perpetrated through smartwatches. We represent crime scenarios in an environment where smartphones are not available, considering that the perception that smartphones can be used as tools for criminal behavior prevails in many organizations, while the potential of similar-use smartwatches is often overlooked. We detail mechanisms for information leakage via file transfer and camera control using smartwatches. Additionally, we present methods to investigate each crime incident through smartwatch forensics. Finally, we describe the limitations of post-incident responses and propose proactive measures to prepare for potential crimes involving smartwatches. Keywords: Information Leakage, Smartwatch Forensics, Android Forensics, Mobile Device Management, Security Polic

Determinants of Esports Highlight Viewership: The Case of League of Legends Champions Korea

Studies on esports league demand via new media platforms are limited yet. This paper is the first to identify determinants of esports highlight viewership. Using set-level highlight view count from YouTube, we analyze various determinants to explain view counts. As a result, we found that the number of kills, playoff games, age of video clip, 2nd round games, and 3rd set is positively correlated to view counts. Outcome uncertainty and upset results do not affect view counts. We interpret the results that as highlight clips are released after the game is finished, viewers can know the results when making a decision. Or, relatively short highlight videos reduce opportunity costs for fans and fans do not care about game outcomes much

Missed a live match? Determinants of League of Legends Champions Korea highlights viewership

This research aims to explore the determinants of the League of Legends Champions Korea (LCK) highlight views and comment counts. The data of 629 game highlight views and comment counts for seven tournaments were collected from YouTube. The highlight views and comment counts were regressed on a series of before-the-game factors (outcome uncertainty and game quality), after-the-game factors (sum and difference of kills, assists, multiple kills, and upset results), and match-related characteristics (game duration, evening game, and clip recentness). A multi-level least square dummy variable regression was conducted to test the model. Among the before-the-game factors, outcome uncertainty and game quality were significantly associated with highlight views and comment counts. This indicated that fans liked watching games with uncertain outcomes and those involving high-quality teams. Among the after-the-game factors, an upset result was a significant determinant of esports highlight views and comment counts. Thus, fans enjoy watching underdogs win. Finally, the sum of kills and assists only affected view counts, which indicated that fans prefer watching offensive games with more kills and a solo performance rather than teamwork

Possible link between Arctic Sea ice and January PM10 concentrations in South Korea

In this study, we investigated the possible teleconnection between PM10 concentrations in South Korea and Arctic Sea ice concentrations at inter-annual time scales using observed PM10 data from South Korea, NCEP R2 data, and NOAA Sea Ice Concentration (SIC) data from 2001 to 2018. From the empirical orthogonal function (EOF) analysis, we found that the first mode (TC1) was a large-scale mode for PM10 in South Korea and explained about 27.4% of the total variability. Interestingly, the TC1 is more dominantly influenced by the horizontal ventilation effect than the vertical atmospheric stability effect. The pollution potential index (PPI), which is defined by the weighted average of the two ventilation effects, is highly correlated with the TC1 of PM10 at a correlation coefficient of 0.75, indicating that the PPI is a good measure for PM10 in South Korea at inter-annual time scales. Regression maps show that the decrease of SIC over the Barents Sea is significantly correlated with weakening of high pressure over the Ural mountain range region, the anomalous high pressure at 500 hPa over the Korean peninsula, and the weakening of the Siberian High and Aleutian low. Moreover, these patterns are similar to the correlation pattern with the PPI, suggesting that the variability of SIC over the Barents Sea may play an important role in modulating the variability of PM10 in South Korea through teleconnection from the Barents Sea to the Korean peninsula via Eurasia

A Study on Facial Expression Change Detection Using Machine Learning Methods with Feature Selection Technique

Along with the fourth industrial revolution, research in the biomedical engineering field is being actively conducted. Among these research fields, the brain-computer interface (BCI) research, which studies the direct interaction between the brain and external devices, is in the spotlight. However, in the case of electroencephalograph (EEG) data measured through BCI, there are a huge number of features, which can lead to many difficulties in analysis because of complex relationships between features. For this reason, research on BCIs using EEG data is often insufficient. Therefore, in this study, we develop the methodology for selecting features for a specific type of BCI that predicts whether a person correctly detects facial expression changes or not by classifying EEG-based features. We also investigate whether specific EEG features affect expression change detection. Various feature selection methods were used to check the influence of each feature on expression change detection, and the best combination was selected using several machine learning classification techniques. As a best result of the classification accuracy, 71% of accuracy was obtained with XGBoost using 52 features. EEG topography was confirmed using the selected major features, showing that the detection of changes in facial expression largely engages brain activity in the frontal regions

Exercise and the Risk of Dementia in Patients with Newly Diagnosed Atrial Fibrillation: A Nationwide Population-Based Study

Background: It is unclear whether exercise would reduce dementia in patients with a new diagnosis of atrial fibrillation (AF). Therefore, we aimed to evaluate the association between the change in physical activity (PA) before and after new-onset AF and the risk of incident dementia. Methods: Using the Korean National Health Insurance Service database, we enrolled a total of 126,555 patients with newly diagnosed AF between 2010 and 2016, who underwent health examinations within two years before and after their diagnosis of AF. The patients were divided into four groups: persistent non-exercisers, exercise starters, exercise quitters, and exercise maintainers. Results: Based on a total of 396,503 person-years of follow-up, 5943 patients were diagnosed with dementia. Compared to persistent non-exercisers, exercise starters (adjusted hazard ratio (aHR) 0.87; 95% confidence interval (CI) 0.81–0.94), and exercise maintainers (aHR 0.66; 95% CI 0.61–0.72) showed a lower risk of incident dementia; however, the risk was similar in exercise quitters (aHR 0.98; 95% CI 0.92–1.05) (p-trend < 0.001). There was a J-shaped relationship between the dose of exercise and the risk of dementia, with the risk reduction maximized at 5–6 times per week of moderate-to-vigorous PA among exercise starters. Conclusion: Patients who initiated or continued regular exercise after diagnosis of AF were associated with a lower risk of dementia than persistent non-exercisers, with no risk reduction associated with exercise cessation. Our findings may provide evidence for the benefit of exercise prescription to patients with new-onset AF to prevent incident dementia regardless of their current exercise status