Abstract-The introduction of the Internet of Things (IoT) in education, which allows Internet based communications to happen between physical objects, sensors and controllers, has changed educational institutions massively. By embedding sensors in objects and integrating cloud computing, augmented reality, wearable technologies and big data in this platform, different parameters of the educational environment can be measured and analysed to provide useful information. It also has created a new interaction between people and the environment in educational organisation. In this research based on the recent IoT projects in education, we will categorize the application of IoT in education into four groups: energy management and real time ecosystem monitoring, monitoring student's healthcare, classroom access control and improving teaching and learning. We will investigate and analyse how this platform has changed the Education Business Model and added new value propositions in such organizations based on the Canvas Business Model.

This study attempts to estimate the potential impacts of climate change on the rice production in Malaysia. The crop model ORYZA2000 was used to simulate rice yield of MR 219 variety in eight granary areas of Malaysia from 1999-2007. The model predicted a reduction in rice yield of 0.36 t ha-1 under the scenario of an increase in temperature by 2°C and at the current CO 2 level of 383 ppm. With the reduction in rice yield, the economic loss to the Malaysian rice industry was estimated at RM162.531 million per year. Under the scenario of increase of CO 2 concentration from 383 to 574 ppm and with 2°C rise in temperature, it can be predicted that there will also be a decline in rice yield by 0.69 t ha-1 and consequently the economic loss will be at RM299.145 million per year for the rice industry. With the above potential impacts, some adaptation and mitigation strategies to overcome the adverse effects of climate change on rice production were recommended.

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Background: Several factors have been reported as risk factors for multiple sclerosis (MS); however, the main causes of the disease are still unknown. A geographical area with a low MS incidence is Ahvaz, Iran. Objectives: The objective of this study was to evaluate the association of several demographic characteristics, family history, and birth month with MS in Ahvaz. Patients and Methods:This was a case-control study including 155 MS cases and 155 controls matched for age, sex, and residential status. The participants were selected randomly, using a systematic method, from the MS patients referred to the MS Society of Khuzestan (Iran). The data collection tool was a standardized questionnaire designed by the authors to assess demographic characteristics. Data were analyzed using descriptive statistics including mean, frequency, and standard deviation and inferential statistical tests including χ 2 , Fisher's exact test, and logistic regression using SPSS version 19. Results: In both cases and controls, no significant associations were found between Arab ethnicity and incidence of MS, marital status and risk of MS in Ahvaz, or more than 15-year residency in Ahvaz, birth in Khuzestan, and month of birth and the risk of MS (P > 0.05). However, there was a marginally significant association between living from birth to age 15 years in Ahvaz and MS (P = 0.05). Furthermore, there was an association between a family history of MS and the risk of MS in Ahvaz (P = 0.02), which was significant in univariate logistic regression (P = 0.006). Conclusions:The findings suggested that according to the ecological conditions of Ahvaz, a family history of MS may increase the risk of developing MS.

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