Design and implementation of a cost-aware and smart oyster mushroom cultivation system

Mushrooms are a nutritious food source, which can play a crucial role in providing affordable sources of proteins, vitamins and minerals for people worldwide, but their cultivation requires extensive training and considerable relevant expertise in order to fine-tune multiple environmental parameters. Internally displaced people in the Northern regions of Syria rely on very small-scale traditional oyster mushroom production, which cannot meet their local demand. Many international and local non-governmental organizations (NGOs) working for Syrian refugees, work on mushroom cultivation projects. They have reported significant difficulties and challenges in mushroom cultivation amongst the targeted beneficiaries. Therefore, the two main questions driving this research are: (1) How can organic mushroom cultivation be promoted using a robust and affordable intelligent mushroom farming system? (2) How can organic mushroom farming practices be simplified to support internally displaced and refugee Syrians? This research evaluates the process of automating mushroom cultivation by designing and implementing a smart oyster (Pleurotus ostreatus) mushroom farming system to remotely monitor and manage environmental parameters, such as temperature, humidity, air quality and illumination, inside the farm. Furthermore, ready and dedicated user-friendly web interfaces were also implemented to enable farmers to remotely monitor and manage their farms through the Internet. As a result, a dependable and cost-effective intelligent oyster mushroom cultivation system was designed and implemented in this work. The system includes remote monitoring and management via user-friendly interfaces. This simplifies mushroom cultivation for not only refugees and displaced communities, but also for mushroom farmers in low-income countries. This work can contribute to the eradication of poverty and hunger, in line with the United Nations Sustainable Development Goals one and two

Efficient Feature Selection for Product Labeling over Unstructured Data

WOS: 000407334500050The paper introduces a novel feature selection algorithm for labeling identical products collected from online web resources. Product labeling is important for clustering similar or same products. Products blindly crawled over the web sources, such as online sellers, have unstructured data due to having features expressed in different representations and formats. Such data result in feature vectors whose representation is unknown and non-uniform in length. Thus, product labeling, as a challenging problem, needs efficient selection of features that best describe the products. In this paper, an efficient feature selection algorithm is proposed for product labeling problem. Hierarchical clustering is used with the state of the art similarity metrics to assess the performance of the proposed algorithm. The results show that the proposed algorithm increases the performance of product labeling significantly. Furthermore, the method can be applied to any clustering algorithm that works on unstructured data

Dietary supplement use among undergraduate male students in health and non-health cluster colleges of a public-sector university in Dammam, Saudi Arabia

Abstract Background Dietary supplements (DS) are nutraceuticals that improve overall health and well-being of an individual as well as reduce the risk of diseases. Evidence indicates a rising prevalence of these products worldwide especially among college students. Studies have reported an increasing use of supplements among Saudi students. However, the scope of those researches was limited to prevalence data. Hence, the aim of our study was to document the prevalence, opinions, attitudes, reasons for use and monthly cost attributed to dietary supplement use. Methods A 3-month cross-sectional study was conducted to evaluate use of dietary supplement among health and non-health college students at a public-sector university in Dammam city, Saudi Arabia. It was conducted using Arabic version of the Dietary supplement questionnaire (DSQ-A). A total of 469 male students responded to the survey giving a response rate of 93.8%. The students were from ten colleges of the university. The data was analyzed by SPSS version 22. The study was approved by Institutional Review Board of Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia (IRB-UGS-2018-05-074). Results The overall prevalence of dietary supplement use in the university was 29.42%. In health cluster colleges, it was reported at 35.91% while in non-health cluster college it was 23.69%. Maintaining general health and well-being was the most common reason for use. Prevalence of multivitamins and whey proteins was approximately 23%. Average monthly cost of supplement was SAR 278.92 (USD 74.39). Cost was positively correlated (ρ = 0.305) with satisfaction score. Students preferred brand products (16.4%). 41.4% students opined that DS may prevent chronic illness if used regularly and agreed that they are good for health. Majority of students (65%) recommended DS use only upon physician’s recommendation. College clusters and study-year was associated (p-value< 0.01) with students’ opinion. Students in health cluster colleges were more likely to recommend supplements (OR 3.715, p-value< 0.0001). Conclusion Prevalence of dietary supplement use was lower than other local and international university students. Health cluster colleges had higher prevalence as compared to non-health cluster colleges. Multivitamins and whey protein were the most commonly used types of DS. Students preferred brand products, had positive opinions and attitudes towards dietary supplement. However, they recommended supplements use to others only upon a physician’s recommendation