Android fine-grained permission control system with real-time expert recommendations

In current Android architecture design, users have to decide whether an app is safe to use or not. Expert users can make savvy decisions to prevent unnecessary privacy breach. However, inexperienced users may not be able to decide correctly. To assist inexperienced users to make a right permission granting decisions, we propose RecDroid. RecDroid is a crowdsourcing recommendation framework that facilitates a user-help-user environment regarding smartphone permission control. In this framework, the responses from expert users are aggregated and recommended to other users. We implement our prototype on Android platform and evaluated the system through simulation and real user study.     

Smartphone habit and behavior in Brunei: Personalization,gender, and generation gap

A smartphone is a device which offers advanced technologies, functions similarly to a computer, supports multitasking and makes it easy to remain connected with others. The following survey design research examined the usage patterns of smartphone users across different demographics. The results of this study provide insights into the prevalence of respondents’ usage of smartphones and their habits and behavior related to smartphone use itself especially among the younger generation of social disorders such as nomophobia and phubbing. In addition to documenting the experience of smartphone users, the research also examines personality patterns related to smartphone usage, the trends of different age groups, and the effects of gender preferences.     

Towards ubiquity in ambient intelligence: User-guided component mobility in the HI architecture

Ambient Intelligence (AmI) systems need to be as transparent as possible, that is, their users should perceive only the effects of the features presented to them and, in some cases, some kind of interface. They should not be conscious of how these features are implemented, from a hardware or from a software point of view.     

Copy-Paste Detection Based on a SIFT Marked Graph Feature Vector

To detect copy-paste tampering, an im-proved SIFT (Scale invariant feature transform)-based al-gorithm was proposed. Maximum angle is defined and a maximum angle-based marked graph is constructed. The m arked graph feature vector is provided to each SIFT key point via discrete polar coordinate transformation. Key points are matched to detect the copy-paste tamper-ing regions. The experimental results show that the pro-posed algorithm can effectively identify and detect the ro-tated or scaled copy-paste regions, and in comparison with the methods reported previously, it is resistant to post-processing, such as blurring, Gaussian white noise and JPEG recompression. The proposed algorithm performs better than the existing algorithm to dealing with scaling transformation.     

Examining the factors that influence early adopters’ smartphone adoption: The case of college students

The influence of early adopters on potential adopters’ decisions of whether or not to adopt a product is known to be critical. In this paper, we examine the factors that influence the adoption behavior of smartphone early adopters by looking at smartphone adoption behavior of college students, because a large portion of the early adopters of smartphones are college students. Our focus is on the effect of normative peer influence on a college student’s smartphone adoption. We also examine the influence of other factors such as self-innovativeness, self-efficacy, the decision maker’s attitudes towards a product, financial burden of using the product, familial influence, and other demographic factors (e.g., age and gender). College students’ adoption behavior is studied using logit and probit choice models developed based on random utility theory. The discrete choice models are empirically estimated using survey data. We find important influence of friends, financial burden, and other family members on the smartphone adoption of college students who adopted smartphones earlier than other students.     

The effect of mobile messaging during a conversation on impression formation and interaction quality

This paper presents two experimental studies investigating the impact of mobile messaging during an offline conversation on relational outcomes. A first study examined the impact on impression formation. A 3 × 1 experiment revealed that phone users were perceived as significantly less polite and attentive, and that self-initiated messaging behavior led to more negative impression formation than messaging behavior in response to a notification. A second study examined the impact on perceived conversation quality and social attraction. A 2 × 2 experiment revealed that perceived conversation quality was negatively affected by co-present mobile messaging behavior, while social attraction was not. Whether persons were acquainted or not with the phone user did not moderate this relationship.     

The sociability score: App-based social profiling from a healthcare perspective

As the smartphone becomes an integral part of our lives, its value as a rich data source reaches an increasing potential. Several previous studies have used smartphone-derived data to discover relationships between user characteristics and different types of smartphone use. However, none tried to use smartphone data to capture an individual's social behavior into one profile, aimed at providing additional information for the diagnostic evaluation of social deficits. This study presents a novel way of combining different modalities of smartphone data for the creation of sociability profiles using a scoring mechanism that allows for easy addition and removal of data sources. Following installation of the smartphone application, data is being sampled in the background to allow for the assessment of spontaneous smartphone use. Sociability scores were based on the integration of social communication and social exploration scores derived from smartphone use and environmental data sampling (e.g., GPS and external Bluetooth signals). Finally, we have applied our Sociability model to create social profiles of ten test subjects as a baseline for future studies. This pilot study provided insight in the usability of the individual sociability scores for future smartphone application to provide longitudinal objective measures of normal and atypical human social behavioral profiles in their natural environment.     

Young drivers’ engagement with social interactive technology on their smartphone: Critical beliefs to target in public education messages

The current study forms part of a larger study based on the Step Approach to Message Design and Testing (SatMDT), a new and innovative framework designed to guide the development and evaluation of health communication messages, including road safety messages. This four step framework is based on several theories, including the Theory of Planned Behaviour. The current study followed steps one and two of the SatMDT framework and utilised a quantitative survey to validate salient beliefs (behavioural, normative, and control) about initiating, monitoring/reading, and responding to social interactive technology on smartphones by N = 114 (88 F, 26 M) young drivers aged 17–25 years. These beliefs had been elicited in a prior in-depth qualitative study. A subsequent critical beliefs analysis identified seven beliefs as potential targets for public education messages, including, ‘slow-moving traffic’ (control belief − facilitator) for both monitoring/reading and responding behaviours; ‘feeling at ease that you had received an expected communication’ (behavioural belief −advantage) for monitoring/reading behaviour; and ‘friends/peers more likely to approve’ (normative belief) for responding behaviour. Potential message content targeting these seven critical beliefs is discussed in accordance with the SatMDT.     

导通孔电镀铜填充技术

概述了下一代PCB用镀铜层导通孔填充技术。     

Smartphone Addiction Inventory (SPAI): Psychometric properties and confirmatory factor analysis

The Smartphone Addiction Inventory (SPAI) was developed to assess smartphone addiction in Taiwanese university students. The purpose of the current research is to evaluate the factor structure and psychometric properties of the SPAI in Italian university students. A total of 485 university students (29.3% boys) completed the SPAI and the Young’s Internet Addiction Test (IAT).The proposed four-factor model of the SPAI-I was tested by computing CFA, and the results of the goodness of fit indices indicated an ambiguous solution. An exploratory-confirmatory cross validation strategy was applied for a better trimming of SPAI-I factorial structure. Results suggested a five-factor solution that explained 53% of the total variance (Time Spent, Compulsivity, Daily Life Interference, Craving, and Sleep Interference). Excellent internal consistency and five factor correlations were reported for the SPAI-I. This five-factor model showed good convergent validity with the Internet Addiction Disorder Test. Considering that evidence shows that overuse of a smartphone can be associated with adverse and problematic effects, the SPAI-I should be useful for determining its potential for the use in future research in Europe and for comparing the evaluation of smartphone overuse of young European people with other international Asiatic studies that have incorporated the SPAI.