Search

Android phones are winding up progressively vital in regular day to day existence and offer a generous assortment of versatile applications for data, correspondence, instruction, and diversion purposes. Android phones ordinarily have contact screens, versatile Internet get to through Wi-Fi or cell systems, ability for establishment of Android phone applications, and different capacities, for example, media players, computerized cameras, and GPS-based route. Mobile devices have spread quickly all around the globally and have become more usually than computers. Modern mobile phones have exceeded the assumption of new technologies. People carry them with their keys and wallets all the time and everywhere. Android phones are no longer just phones; they have become multiple purpose tools. People use them to call, take pictures, record videos or audio, play music, browse the Internet, check the weather, find directions, translate a word, read an e-book, play a game, attend a virtual class, and even read a product price. The main aim of this study is to assess the purpose behind the use of Android phone by medical students, also explore barriers while using the mobile for education purpose. The nature of this study was quantitative; questionnaire was used as data collection tool which was developed by researchers. Simple random sampling technique was used to collect the data from target population.The results of this study found that the use of Android phone for education purpose was very good in selected university, but it needed more attention of higher administration to support the use of mobile phone as tools which help in the promotion in medical education among medical students. [ABSTRACT FROM AUTHOR]

New spectral absorption photometry methods are introduced to estimate chlorophyll (Chl) content of corn leaves by smart phones. The first method acquires light passing through a leaf by smartphone camera, compensating for differences in illumination conditions. In order to improve performance of the method, spectral absorption photometry (SAP) with background illumination has been considered as well. Data were acquired by smartphone camera in Iowa State University maize fields. Various indices were extracted and their correlation with Chl content were examined by Minolta SPAD-502. Hue index in SAP reached R value of 0.59. However, with light-aided SAP (LASAP), R of 0.97 was obtained. Among traits, the vegetation index gave the most accurate indication. We can conclude that the high performance of LASAP method for estimating Chl content, leads to new opportunities offered by smart phones at much lower cost. This is a highly accurate alternative to SPAD meters for estimating Chl content nondestructively. [ABSTRACT FROM AUTHOR]

Abstract: As the number of smartphone users has grown recently, many context-aware services have been studied and launched. Activity recognition becomes one of the important issues for user adaptive services on the mobile phones. Even though many researchers have attempted to recognize a user's activities on a mobile device, it is still difficult to infer human activities from uncertain, incomplete and insufficient mobile sensor data. We present a method to recognize a person's activities from sensors in a mobile phone using mixture-of-experts (ME) model. In order to train the ME model, we have applied global–local co-training (GLCT) algorithm with both labeled and unlabeled data to improve the performance. The GLCT is a variation of co-training that uses a global model and a local model together. To evaluate the usefulness of the proposed method, we have conducted experiments using real datasets collected from Google Android smartphones. This paper is a revised and extended version of a paper that was presented at HAIS 2011. [Copyright &y& Elsevier]