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Remote pointing is an interaction style for presentation systems, interactive TV, and other systems where the user is positioned an appreciable distance from the display. A variety of technologies and interaction techniques exist for remote pointing. This paper presents an empirical evaluation and comparison of two remote pointing devices. A standard mouse is used as a base-line condition. Using the ISO metric throughput (calculated from users' speed and accuracy in completing tasks) as the criterion, the two remote pointing devices performed poorly, demonstrating 32% and 65% worse performance than the mouse. Qualitatively, users indicated a strong preference for the mouse over the remote pointing devices. Implications for the design of present and future systems for remote pointing are discussed.

Abstract-The purpose of this study is to investigate the use and effects of smartphones on academic staffs at a university level, especially in the Kingdom of Saudi Arabia. We conducted a survey study using questionnaires. The questionnaires were randomly distributed to 66 academic staffs who own a smartphone at the Northern Border University. This study discovers the smartphone had replaced a computer, and an email application was mostly used. The academic staffs also had utilized smartphone as a means for knowledge sharing. Social media applications were greatly used in teaching and learning. Despite the benefits of smartphone use, academic staffs had been negatively affected. This study also reveals that having a smartphone diverted academic staffs' focus at work, created "check habits", and an artificial relationship; more than 90% of the respondents admitted that they put their smartphone besides their bed before sleep, and 61.41% of them claimed that they had the feelings of incompleteness whenever smartphones were not with them.

Abstract-Advancement of mobile technologies such as smartphones and PC tablets has given a great impact on healthcare systems. The mobile technology offers innovative approaches to addressing complex health concerns. Many mobile health applications (mHealth apps) are currently available on marketplaces. These apps are designed to facilitate various health issues and problems, and are intended to be used outside clinics. However, very little research has been conducted to address trend, opportunities, and challenging issues of the apps. The purpose of this study is to investigate the current state of mHealth. A literature survey was conducted. Major findings of this study include, smartphones will be the major platform for mHealth apps, the number of published software is much higher than published scientific research, current mHealth apps lacking in grounded based theory and evaluation, and security and usability issues are still vulnerable. The findings suggest that involvement of all healthcare stakeholders is critical to the success of mHealth apps.Keywords-mHealth apps; mobile computing; smartphoness IntroductionMobile technology has changed and will continue to change the life of millions of people around the globe. It is a technology which allows a computing device not to be connected to any fixed physical link. Examples of mobile computing devices are smartphones, laptops, tablets, e-book readers, cameras, and so on; the most powerful and attractive one is smartphones. It incorporates all aspects of computing application and wireless communications.Nearly 85% of the world population will have access to 3G wireless coverage, with the half of the population living in areas with 4G networks in year 2017 [1]. The growth of smartphones has far-reaching implications for eHealth [2]. The word eHealth was defined in [3] as "a relation to health services delivery such as healthcare, health system, health sector or health industry which suggests that eHealth refer more to services and systems rather than to the health of people". Smartphones have become a common device in healthcare settings; leading to rapid growth in the development of mHealth apps [4].

Background With the development of today’s technology, and as humans tend to naturally use hand gestures in their communication process to clarify their intentions, hand gesture recognition is considered to be an important part of Human Computer Interaction (HCI), which gives computers the ability of capturing and interpreting hand gestures, and executing commands afterwards. The aim of this study is to perform a systematic literature review for identifying the most prominent techniques, applications and challenges in hand gesture recognition. Methodology To conduct this systematic review, we have screened 560 papers retrieved from IEEE Explore published from the year 2016 to 2018, in the searching process keywords such as “hand gesture recognition” and “hand gesture techniques” have been used. However, to focus the scope of the study 465 papers have been excluded. Only the most relevant hand gesture recognition works to the research questions, and the well-organized papers have been studied. Results The results of this paper can be summarized as the following; the surface electromyography (sEMG) sensors with wearable hand gesture devices were the most acquisition tool used in the work studied, also Artificial Neural Network (ANN) was the most applied classifier, the most popular application was using hand gestures for sign language, the dominant environmental surrounding factor that affected the accuracy was the background color, and finally the problem of overfitting in the datasets was highly experienced. Conclusions The paper will discuss the gesture acquisition methods, the feature extraction process, the classification of hand gestures, the applications that were recently proposed, the challenges that face researchers in the hand gesture recognition process, and the future of hand gesture recognition. We shall also introduce the most recent research from the year 2016 to the year 2018 in the field of hand gesture recognition for the first time.

Fusion technologies have rapidly evolved. These technologies are normally customized according to the needs of domains. Despite a large number of publications on intelligence fusion applications for various domains, they are scattered. The aim of this review is to present the state of the art for intelligence fusion applications within a specific domain. We identified three major domains for the purpose, namely robotics, military, and healthcare, during the initial process of the systematic review. These three domains are always in need of superior intelligence. Articles were searched mainly in IEEE Xplore. We limit the range of publications to the year 2014 to 2019, to focus on the most recent publications. We adopt the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to screen, filter and evaluate qualities of each retrieved article. As a result, we retrieved 675 articles at the initial stage of the search, we conducted screening and filtering process and reviewed 153 articles potential articles, and finally, we excluded 36 articles as they do not comply with our quality assessment criteria. Only 117 articles are included. The results of this study are a list of classified applications within the domains and a number of relevant techniques or approaches used in each classified application. The finding of this review showed that the most published works for the use of intelligence fusion are mainly applications in the robotics domain, where mostly used techniques are Kalman Filter and its variants. Outcomes of this study can be a guideline or an insight for researchers to further develop and implement in this field.

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