Validity,Reliability,and Measurement Invariance of the Thai Smartphone Application-Based Addiction Scale and Bergen Social Media Addiction Scale

Background:In recent years,there has been increased research interest in both smartphone addiction and social media addiction as well as the development of psychometric instruments to assess these constructs.However,there is a lack of psychometric evaluation for instruments assessing smartphone addiction and social media addiction in Thailand.The present study evaluated the psychometric properties and gender measurement invariance of the Thai version of the Smartphone Application-Based Addiction Scale(SABAS)and Bergen Social Media Addiction Scale(BSMAS).Method:A total of 801 Thai university students participated in an online survey from January 2022 to July 2022 which included demographic information,SABAS,BSMAS,and the Internet Gaming Disorder Scale-Short Form(IGDS9-SF).Results:Confirmatory Factor Analyses(CFAs)found that both the SABAS and BSMAS had a one-factor structure.Findings demonstrated adequate psychometric properties of both instruments and also supported measurement invariance across genders.Moreover,scores on the SABAS and BSMAS were correlated with scores on the IGDS9-SF.Conclusion:The results indicated that the SABAS and BSMAS are useful psychometric instruments for assessing the risk of smartphone addiction and social media addiction among Thai young adults.

Investigation of Inside-Out Tracking Methods for Six Degrees of Freedom Pose Estimation of a Smartphone in Augmented Reality

Six degrees of freedom(6DoF)input interfaces are essential formanipulating virtual objects through translation or rotation in three-dimensional(3D)space.A traditional outside-in tracking controller requires the installation of expensive hardware in advance.While inside-out tracking controllers have been proposed,they often suffer from limitations such as interaction limited to the tracking range of the sensor(e.g.,a sensor on the head-mounted display(HMD))or the need for pose value modification to function as an input interface(e.g.,a sensor on the controller).This study investigates 6DoF pose estimation methods without restricting the tracking range,using a smartphone as a controller in augmented reality(AR)environments.Our approach involves proposing methods for estimating the initial pose of the controller and correcting the pose using an inside-out tracking approach.In addition,seven pose estimation algorithms were presented as candidates depending on the tracking range of the device sensor,the tracking method(e.g.,marker recognition,visual-inertial odometry(VIO)),and whether modification of the initial pose is necessary.Through two experiments(discrete and continuous data),the performance of the algorithms was evaluated.The results demonstrate enhanced final pose accuracy achieved by correcting the initial pose.Furthermore,the importance of selecting the tracking algorithm based on the tracking range of the devices and the actual input value of the 3D interaction was emphasized.

Logical Image Acquisition and Analysis of Android Smartphones

Android smartphones largely dominate the smartphone market. For this reason, it is very important to examine these smartphones in terms of digital forensics since they are often used as evidence in trials. It is possible to acquire a physical or logical image of these devices. Acquiring physical and logical images has advantages and disadvantages compared to each other. Creating the logical image is done at the file system level. Analysis can be made on this logical image. Both logical image acquisition and analysis of the image can be done by software tools. In this study, the differences between logical image and physical image acquisition in Android smartphones, their advantages and disadvantages compared to each other, the difficulties that may be encountered in obtaining physical images, which type of image contributes to obtaining more useful and effective data, which one should be preferred for different conditions, and the benefits of having root authority are discussed. The practice of getting the logical image of the Android smartphones and making an analysis on the image is also included. Although root privileges are not required for logical image acquisition, it has been observed that very limited data will be obtained with the logical image created without root privileges. Nevertheless, logical image acquisition has advantages too against physical image acquisition.

SmartPhone类手机应用开发框架研究

通过对SmartPhone类型手机的研究与消息机制的分析,最终创建起较为通用高效的开发框架,对于后继软件开发建立了良好的开发平台.

使用VB2005设计Smartphone智能手机应用程序入门

Smartphone是一个兴起中的智能手机系统,Microsoft将智能手机编程赋予给高级语言编程系统VB2005,实现了大众化的程序开发。通过实例分析,从Smartphone程序的界面设计、程序代码编写,到程序的调试、应用,适合程序员的入门使用。

一种基于Smartphone类的注册表实现方案

目前Smartphone类型的手机注册表都是用数据库实现的,现在要改用COMS来实现,具体做法是采用大小为64KB的2块FLASH来模拟CMOS,在此基础上实现注册表的管理,直接从FLASH驱动层做起。注册表的记录改变了传统的Windows做法,采用一种简化的方法,不分目录级,由一个主键加一个键值构成,其主键是一个null结束的字符串,可以包含目录信息,这对后继手机软件的应用开发建立了良好的开发基础。

基于Windows CE 的Smartphone操作系统界面响应研究

本文在.NET Compact Framework环境下结合Visual Studio 2008开发了一个基于Windows CE平台的Smartphone操作系统主题自制软件,对其中的界面响应问题做了简要阐述,并给出了解决办法。

基于Windows CE的Smartphone操作系统图片研究

本文在.NET Compact Framework环境下结合Visual Studio 2008开发了一个基于Windows CE平台的Smartphone操作系统主题自制软件,对其中的图片选取、图片路径获得及图片加载时遇到的问题做了简要阐述,并给出了这些问题的解决办法。

Predictive Factors for Smartphone Dependence: Relationship to Demographic Characteristics, Chronotype, and Depressive State of University Students

We investigated factors contributing to smartphone dependence. To 196 medical university students, we administered a set of self-reporting questionnaires designed to evaluate demographic characteristics, smartphone dependence, chronotype, and depressive state. Smartphone dependence was evaluated using the Wakayama Smartphone-Dependence Scale (WSDS) with 3 subscales: Subscale 1, immersion in Internet communication;Subscale 2, using a smartphone for extended periods of time and neglecting social obligations and other tasks;Subscale 3, using a smartphone while doing something else and neglect of etiquette. Multiple regression analyses revealed that living in a family, eveningness, and presence of depression were associated with Subscale 1, that living in a family and eveningness were also associated with Subscale 2, and that being a man was associated with Subscale 3. These findings suggest that smartphone dependence can be predicted by factors such as gender, mode of residence, chronotype, or depressive state.

Development of Japanese Version of Smartphone Dependence Scale

We designed a Japanese version of the Smartphone Dependence Scale (J-SDS) for university students, and assessed its validity and reliability. For development of this scale, we initially selected 43 preliminary items based on previous studies of Internet and mobile phone dependence. Each response was scored using a Likert scale (0, 1, 2, 3), with higher scores indicating greater dependence. After administering the preliminary scale to 149 university students, the final 29 items were selected according to exploratory factor analysis. The final scale consisted of 5 factors: 1) craving and withdrawal, 2) overuse and tolerance, 3) virtual life orientation, 4) disturbance of concentration in class, and 5) physical symptoms. Reliability coefficient (Cronbach’s alpha) values for the 5 factors and total J-SDS were 0.87, 0.87, 0.76, 0.77, 0.69, and 0.92, respectively. We then summed the Likert scores for each item to provide a quantitative overall smartphone dependence score, with higher scores indicating greater dependence. The J-SDS score became significantly higher with longer hours of smartphone use (p < 0.001). Our results suggest that the J-SDS is a reliable and valid scale for screening university students who may be at risk of developing smartphone dependence.

Relationship of Smartphone Dependence to General Health Status and Personality Traits among University Students

We investigated associations between smartphone dependence and general health status or personality traits. To 197 medical university students, we administered a set of self-reporting questionnaires designed to evaluate these parameters. For males, smartphone dependence positively correlated with somatic symptoms, anxiety and insomnia, and emotional instability, and negatively correlated with agreeableness. For females, smartphone dependence positively correlated with somatic symptoms, severe depression, and extraversion, and negatively correlated with social dysfunction. These findings suggest that smartphone dependence may be associated with general health status or personality traits and that there may be a gender difference in these associations.

基于Smartphone的嵌入式应用程序开发初探

智能手机发展迅速,基于智能手机的应用程序开发也逐渐多起来,本文主要介绍Microsoft的Smartphone智能手机平台,以及基于此平台使用Visual Studio.NET进行应用程序的开发的方法。

“聪明”手机三十计 精选30款Smartphone软件

Smartphone操作系统是智能手机操作系统的一种，与采用其他智能手机操作系统的手机相同的是，Smartphone手机也同样具有良好的软件扩展性。换而言之，我们可以通过安装各种各样适合Smartphone手机的软件，使Smartphone手机增加许多原来没有而我们希望获得的功能。到哪里去找我们需要的Smartphone软件呢？相信这是困扰许多Smartphone手机用户的问题，本期小编就特别搜罗了一些Smartphone软件，并且加以精选分类，希望对广大Smartphone手机用户能有所帮助。

Smartphones,tele-ophthalmology,and VISION 2020

Telemedicine is an emerging field in recent medical achievements with rapid development. The ＂smartphone＂ availability has increased in both developed and developing counffies even among people in rural and remotes areas. Telebased services can be used for screening ophthalmic diseases and also monitoring patients with known diseases. Electronic ophthalmologic records of the patients including captured images by smartphones from anterior and posterior segments of the eye will be evaluated by ophthalmologists, and if patients require further evaluations, they will be referred to experts in the relevant field. Eye diseases such as cataract, glaucoma, age-related macular degeneration, diabetic retinopathy, and retinopathy of prematurity are the most common causes of blindness in many countries and beneficial use of teleophthalmology with smartphones will be a good way to achieve the aim of VISION 2020 all over the world. Numerous studies have shown that teleophthalmology is similar to the conventional eye care system in clinical outcomes and even provides more patient satisfaction as it saves time and cost, This review explains how teleophthalmology helps to improve patient outcomes through smartphones.

Smartphone-Imaged HIV-1 Reverse-Transcription Loop-Mediated Isothermal Ampliflcation(RT-LAMP) on a Chip from Whole Blood

Viral load measurements are an essential tool for the long-term clinical care of human immunodeficiency virus （HIV）-positive individuals. The gold standards in viral load instrumentation, however, are still too limited by their size, cost, and sophisticated operation for these measurements to be ubiquitous in remote settings with poor healthcare infrastructure, including parts of the world that are disproportionately affected by HIV infection. The challenge of developing a point-of-care platform capable of making viral load more accessible has been frequently approached but no solution has yet emerged that meets the practical requirements of low cost, portability, and ease-of-use. In this paper, we perform reverse-transcription loop-mediated isothermal amplification （RT-LAMP） on minimally processed HIV-spiked whole blood samples with a microfluidic and silicon microchip platform, and perform fluorescence measurements with a consumer smartphone. Our integrated assay shows amplification from as few as three viruses in a - 60 nL RT- LAMP droplet, corresponding to a whole blood concentration of 670 viruses per μL of whole blood. The technology contains greater power in a digital RT-LAMP approach that could be scaled up for the determination of viral load from a finger prick of blood in the clinical care of HIV-positive individuals. We demonstrate that all aspects of this viral load approach, from a drop of blood to imaging the RT-LAMP reaction, are compatible with lab-on-a-chip components and mobile instrumentation.

Smartphone-based cytometric biosensors for point-of-care cellular diagnostics

Analysis on a single-cell basis is both fundamental and meaningful in biomedical research and clinical practice.Flow cytometry is one of the most popular approaches in this field with broad applications in cell sorting,counting,and identification of rare cells.However,the complicated design and bulky size of conventional flow cytometry have restricted their applications mainly in centralized laboratories.With the recent development of smartphone devices,smartphone-based cytometry has been explored and tested for single-cell analysis.Compared with traditional cytometers,smartphone-based cytometric biosensors are more suitable for point-of-care(POC)uses,such as on-site disease diagnosis and personal health monitoring.In this review article,the history of traditional flowcytometry is introduced,and advances of smartphone-enabled cytometry are summarized in detail based on different working principles.Representative POC applications of smartphone cytometers are also discussed.The achievements demonstrated so far illustrate the potential of smartphone-based cytometric devices to transform single-cell measurement in general,with a significant impact in POC diagnostics,preventive medicine,and cell biology.

Surveying ionizing radiations in real time using a smartphone

Surveying ionizing radiations of the surrounding with a smartphone provides a low-cost and convenient utility for the general public. We developed a smartphone application(App) that uses the built-in camera with a CMOS sensor and a radiation signal extraction algorithm.After a calibration through a series of radiation exposures,the App could display radiation dose rate and cumulative dose in real time without requiring covering the camera lens. A smartphone with this App can be used as a fast survey tool for ionizing radiations.

Investigation of children’s habits of smartphone usage and parental awareness of myopia control in underdeveloped areas of China

AIM: To investigate the behaviors of smartphone usage and parental knowledge of vision health among primary students in the rural areas of China. METHODS: In this school-based, cross-sectional study, a total of 52 606 parents of students from 30 primary schools in the Xingguo County were investigated through an online questionnaire from July 2020 to August 2020. The self-designed questionnaire contained three parts: the demographic factors of both children and parents, parental knowledge and attitude toward myopia, and the preventive treatment of myopia.RESULTS: A total of 52 485 appropriately answered questionnaires were received, showing an effective response rate of 95.1%. The average age of the primary students was 10.1±0.98 y and the prevalence of myopia among the primary students was 40.3%. The age of myopia occurrence in elementary students was significantly correlated with the parents’ educational level(95%CI: 0.82-0.98, P=0.013), children’s gender(95%CI: 1.08-1.20, P<0.001), school location(county or countryside)(95%CI: 0.59-0.66, P<0.001), children’s smartphone ownership(95%CI: 1.09-1.26, P<0.001), and the average time spent on smartphone per day(95%CI: 0.78-0.88, P<0.001). School location in the county town, high family income, and high parents’educational level significantly affected both parents’ myopia awareness and children’s vision-threatening behaviors(P<0.01). Left-behind children showed a higher incidence of vision-threatening habits than those who lived with their parents(P<0.01).CONCLUSION: The results reveal the current situation of myopia development among rural primary school students and their parents. This survey will serve as a guidance for designing myopic prevention policies in the rural areas of China.

Implementation of a Smartphone as a Wearable and Wireless Accelerometer and Gyroscope Platform for Ascertaining Deep Brain Stimulation Treatment Efficacy of Parkinson’s Disease through Machine Learning Classification

Parkinson’s disease manifests in movement disorder symptoms, such as hand tremor. There exists an assortment of therapy interventions. In particular deep brain stimulation offers considerable efficacy for the treatment of Parkinson’s disease. However, a considerable challenge is the convergence toward an optimal configuration of tuning parameters. Quantified feedback from a wearable and wireless system consisting of an accelerometer and gyroscope can be enabled through a novel software application on a smartphone. The smartphone with its internal accelerometer and gyroscope can record the quantified attributes of Parkinson’s disease and tremor through mounting the smartphone about the dorsum of the hand. The recorded data can be then wirelessly transmitted as an email attachment to an Internet derived resource for subsequent post-processing. The inertial sensor data can be consolidated into a feature set for machine learning classification. A multilayer perceptron neural network has been successfully applied to attain considerable classification accuracy between deep brain stimulation “On” and “Off” scenarios for a subject with Parkinson’s disease. The findings establish the foundation for the broad objective of applying wearable and wireless systems for the development of closed-loop optimization of deep brain stimulation parameters in the context of cloud computing with machine learning classification.

Smartphone User Authentication Based on Holding Position and Touch-Typing Biometrics

In this advanced age,when smart phones are the norm,people utilize social networking,online shopping,and even private information storage through smart phones.As a result,identity authentication has become the most critical security activity in this period of the intelligent craze.By analyzing the shortcomings of the existing authentication methods,this paper proposes an identity authentication method based on the behavior of smartphone users.Firstly,the sensor data and touch-screen data of the smart phone users are collected through android programming.Secondly,the eigenvalues of this data are extracted and sent to the server.Thirdly,the Support Vector Machine(SVM)and Recurrent Neural Network(RNN)are introduced to train the collected data on the server end,and the results are finally yielded by the weighted average.The results show that the method this paper proposes has great FRR(False Reject Rate)and FAR(False Accept Rate).