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This paper describes an experimental study of the friction generated between compacted maize and smooth ridge counterfaces. The influence of compaction conditions and the normal load is presented for a hemispherical compact in contact with a smooth rigid plane. The data are analysed using the approaches which have been widely adopted to interpret the friction of rough solid bodies. The compact surface is an interesting and structurally simple case of a rough solid surface. These analyses are shown to provide a good prediction of the friction and its load dependence.

When the learners are truly interested in learning, they learn faster, participate actively, and they pull knowledge. Unlike school education, adult learning mostly occurs with the initiation of the adult learner, and they then pull the relevant knowledge. Vocational education is the master key that opens the door to the economic and social development of a country and it provides an opportunity for Bottom of Pyramid people (BOP) to acquire a sustainable livelihood. Due to many difficulties and commitments of their lives, BOP people are not engaging in a continuous learning process. Since there are many adaptive mobile learning systems available, there is no proper mechanism to achieve the sustainable livelihood of BOP people through vocational education which is tightly coupled with their lifestyle and motivates them to get in learning activities. The context aware adaptive mobile learning framework is an attempt to push vocational knowledge for Bottom of Pyramid (BOP) people, who are not ready to pull knowledge. In this paper, we present mobile learning content design, concept design, system architecture, Adaptivity components, the system implementation and evaluation of the system This system guides BOP people in their vocations through adaptive content delivery mechanisms using mobile technology together with vocational and motivational factors to educate the user in a transparent and non-resistive manner. Social science based models integrated into systems to carry out adaptive delivery of content based on the end user learning behavior, vocation, social and psychological factors.

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Forensic investigations on cloud platforms are an oft-discussed topic in current digital forensics. Significant growth in cloud platforms is expected in the coming decade. With such growth, cloud forensic investigations may require substantial changes in their approach. The paper surveys the most mentioned issues in cloud forensic literature. It is followed by a description of some of our current work aimed at solving those issues. The first issue that we tried to analyze was the issue of the trustworthiness of the evidence. We identified that the trustworthiness of the Cloud Service Providers is hardly discussed in the literature. Based on previous publications on similar issues on standalone computers, we provided an algorithm as an initial answer to the issue. The algorithm checks for the integrity of the evidence which will be affected in a tampering attempt. The next issue that we considered was time-taken for analysis (time complexity of forensic tools). While the issue has been indicated many times in the literature, we did not find many detailed experiments conducted with tools to observe the processing time over data source size. Therefore, the paper includes the results of an experiment that was performed using an Autopsy forensic tool to measure the time complexity of its operation with a number of source files with increasing sizes. Results indicated that the analyzing times usually increased with the size of the source file and that it might become unmanageable with increasing sizes.