Specific smartphone uses and how they relate to anxiety and depression in university students: a cross-cultural perspective

ABSTRACT

People around the world spend hours of their daily lives using smartphones; therefore, it is important to conduct cross-cultural research on the effects of smartphone use on health and well-being as culture influences values, motivations and communication patterns. The purpose of this study was to explore 5 popular uses of the smartphone – messaging, browsing the Internet, posting social content, reading social content, and playing games – how they relate to anxiety and depression scores, and how they vary depending on the country of the participants: Spain, the United States, and Colombia. In all three countries the ranking of most popular uses was the same: (1) Messaging, (2) Reading social content, and (3) Browsing the Internet. In the USA, game playing contributed to anxiety scores whereas reading social content was a protective factor; regarding depression scores, text messaging was a contributing factor. In Spain, browsing the Internet contributed to anxiety scores; regarding depression scores, messaging was a contributing factor and posting social content was a protective factor. In Colombia, no specific use influenced anxiety scores; regarding depression scores, only game playing was a protective factor. Our results showed that in all the countries, problematic smartphone use contributed to anxiety scores.     

Epidemic contact tracing with smartphone sensors

ABSTRACT

Contact tracing is widely considered as an effective procedure in the fight against epidemic diseases. However, one of the challenges for technology based contact tracing is the high number of false positives, questioning its trust-worthiness and efficiency amongst the wider population for mass adoption. To this end, this paper proposes a novel, yet practical smartphone-based contact tracing approach, employing WiFi and acoustic sound for relative distance estimate, in addition to the air pressure and the magnetic field for ambient environment matching. We present a model combining six smartphone sensors, prioritising some of them when certain conditions are met. We empirically verified our approach in various realistic environments to demonstrate an achievement of up to 95% fewer false positives, and 62% more accurate than Bluetooth-only system. To the best of our knowledge, this paper was one of the first work to propose a combination of smartphone sensors for contact tracing.     

Fingerprint optimization method for the indoor localization system

The accuracy of the indoor localization is influenced directly by the quality of the fingerprint. But the indoor localization algorithms in existence are almost conducted based on the original fingerprint which is not optimized. The k-means is introduced to optimize the fingerprint in this paper. And deleting the collected bad-points through the theory of cluster could make the fingerprint more accurate for the indoor localization algorithm. Compared with the indoor localization systems in existence, the result of experiments shows that the optimized fingerprint can increase the accurate of indoor localization with a higher probability.     

CBSC: A Crowdsensing System for Automatic Calibrating of Barometers

The mobile crowdsensing software systems can complete large-scale and complex sensing tasks with the help of the collective intelligence from large numbers of ordinary users. In this paper, we build a typical crowdsensing system, which can efficiently calibrate large numbers of smartphone barometer sensors. The barometer sensor now becomes a very common sensor on smartphones. It is very useful in many applications, such as positioning, environment sensing and activity detection. Unfortunately, most smartphone barometers today are not accurate enough, and it is rather challenging to efficiently calibrate a large number of smartphone barometers. Here, we try to achieve this goal by designing a crowdsensingbased smartphone calibration system, which is called CBSC. It makes use of low-power barometers on smartphones and needs few reference points and little human assistant. We propose a hidden Markov model for peer-to-peer calibration, and calibrate all the barometers by solving a minimum dominating set problem. The field studies show that CBSC can get an accuracy of within 0.1 hPa in 84% cases. Compared with the traditional solutions, CBSC is more practical and the accuracy is satisfying. The experience gained when building this system can also help the development of other crowdsensing-based systems.     

Characterization of cloud cover with a smartphone camera

A smartphone sky camera and associated image analysis algorithm has been developed and validated to determine total cloud cover and the percentage of thick and thin clouds using supervised image classification for a range of cloud types, cloud cover from 4% to 98%, and solar zenith angles between 6° and 49°. Additionally, this system provides the percentage of total, thick, and thin clouds in proximity to the solar disc. The measurement errors were comparable to those associated with values obtained by commercial sky camera systems. The benefits of increasing the availability of cloud fraction measurements include the potential to develop improved local ultraviolet indices and weather forecasts and to provide a better understanding of cloud patterns required for the generation of solar energy.     

Optimal display color for nighttime smartphone users

The study investigated the optimal display color for comfortable use of smartphones at night under low illuminance, while not distorting the perceived quality of displays. Two phases of psychophysical experiments were conducted to judge perceptibility and acceptability of the displays in various shades of white. The experimental results showed that the scores in acceptability were always higher than those in perceptibility all across the hues, and yellow received the highest scores in acceptability among the six hue categories. This can be interpreted that the observers have the intention of using a display in a yellow shade of white even though it is not perceived as pure white. Through the analysis, a white in yellow shade with the RGB values of 255, 255, and 230 was determined as the optimal display color for nighttime smartphone users regardless of display luminance or contents. The proposed display color supports physiological comfort by reducing the blue light, which involves an adverse effect on the biological system, and provides psychological satisfaction by allowing users to decide the color within the range of the user's acceptable threshold. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 60–67, 2017     

Books Received for Review

Smartphone image sensor response is compared for broadband and narrowband (340 nm and 380 nm) UVA wavelengths (320–400 nm) based on previous studies that have demonstrated quantitative response to solar radiation at 380 nm and 340 nm to reconstruct broadband irradiance. This article compares broadband and narrowband sensing using a common readily accessible smartphone equipped with a broadband UVA filter that displayed strong sensitivity to long wavelength UVA irradiances from 370 nm with a maximum at 380 nm. However, the use of narrow passband and neutral density filters allowed quantitative observations at the biologically significant wavelength of 340 nm. Narrow passband filter observations also had less variation at 340 nm than observed for broadband measurements. The results indicate that the smartphone image sensor, with the addition of narrow passband and neutral density filters, is a viable tool for UVA observations, but is unsuitable for broadband filter measurements.     

Minimum required angular resolution of smartphone displays for the human visual system

There has been a rapid increase in the resolution of small‐sized and medium‐sized displays. This study determines an upper discernible limit for display resolution. A range of resolutions varying from 254–1016 PPI were evaluated using simulated display by 49 subjects at 300 mm viewing distance. The results of the study conclusively show that users can discriminate between 339 and 508 PPI and in many cases between 508 and 1016 PPI.     

基于智能手机的实时跌倒检测系统研究

为减少跌倒对老年人造成的伤害,并对跌倒进行实时检测,提出了一种基于Android智能手机的人体跌倒检测系统,手机安置于腰上采集手机加速度传感器数据,利用了姿态识别和跌倒检测相结合的算法,区分出跌倒行为和人体日正常常活动。当检测到异常跌倒时,报警信息以及从手机中GPS获取的位置被发送。仿真及实验表明：系统能够有效地识别出跌倒和日常行为,算法具有较高实时性、具有较高灵敏度和特异度。     

Android手机自动化性能测试工具的研究与开发

针对手机性能测试中效率低、工作量大等问题,提出自动化性能测试的方法,并运用这一方法设计了Android平台手机性能测试的FLEX-ANDROID工具。对这一工具的组成结构和测试脚本的编写进行了详细研究,并且对如何计算和生成测试结果进行了分析说明。通过使用自行研发的FLEX-ANDROID工具进行自动化测试,并将自动化测试所花时间和手动测试时间进行对比,结果表明,自动测试速度大约为手动测试速度的3倍。这表明FLEX-ANDROID工具能够有效提升测试工作效率,大幅度缩减测试时间,减少测试工作的重复劳动。