Human activity recognition is one of the popular research fields. The results of this study can be applied to many other fields such as the military, commercialism, and health. With the advent of the wearable head mounted display device mainly like google glass raises the possibility of this research. In this study tries to identify everyday activities are often called the ambient activity. Development of the system is done online using a smartphone and a head mounted display. The system produces an accuracy above 90%, which can be concluded that the system was able to recognize the activities with great accuracy.

<p>The rapid growing adoption of android operating system around the world affects the growth of malware that attacks this platform. One possible solution to overcome the threat of malware is building a comprehensive system to detect existing malware. This paper proposes multilayer perceptron artificial neural network trained with backpropagation algorithm to determine an application is malware or non-malware application which is often called benign application. The parameters that used in this study based on the list of permissions in the manifest file, the battery rating based on permission, and the size of the application file. Final weights obtained in the training phase will be used in mobile applications for malware detection. The experimental results show that the proposed method for detection of malware on android is effective. The effectiveness is demonstrated by the results of the accuracy of the system developed in this study is relatively high to recognize existing malware samples.</p>

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Visual Impairment persons have the disadvantage when they try to walk straight without any active or passive guidance. They usually tend to walk with circle path how hard they try, this is called veering behavior and it is nature in human instinct. For walking, most visual impairment persons will use at least a support cane for their walking guidance. In Running Athletics para-competition, visual impairment athletes did not use a support cane, they will use human assistant and run together beside them. The athletes will hold tether where the other end were held by the assistant, whose called sighted guide. Some visual impairment school in Indonesia have some difficulties to train their runner athletes, one of them is the limitation of human running assistant provide by them. Blind Runner Guide Android Mobile Application offering one great feature for the visual impairment persons. This application will assist users to stay straight during their walk or run. This application still however can only be used for straight run competition, not circle athletic path which is usually used in international standard competition. This paper review the Visual Impairment user experiences using the application. From the experiment results shows that the application could reduce more than 50% percent of veering behavior. Experiment results from the short version UEQ shows 1.625 mean pragmatic quality score (good benchmark), 0.625 hedonic quality score (bad benchmark), and 1.17 overall quality score (above average benchmark).