Asif Khan¹, Nada Boudjellal², Huaping Zhang^1,*, Arshad Ahmad³, Maqbool Khan³

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3037-3055, 2023, DOI:10.32604/cmc.2023.044403

Abstract Predicting election outcomes is a crucial undertaking, and various methods are employed for this purpose, such as traditional opinion polling, and social media analysis. However, traditional polling approaches often struggle to capture the intricate nuances of voter sentiment at local levels, resulting in a limited depth of analysis and understanding. In light of this challenge, this study focuses on predicting elections at the state/regional level along with the country level, intending to offer a comprehensive analysis and deeper insights into the electoral process. To achieve this, the study introduces the Location-Based Election Prediction Model (LEPM), which utilizes social media data,… More >

Reham Alabduljabbar^*

Computer Systems Science and Engineering, Vol.40, No.1, pp. 1-16, 2022, DOI:10.32604/csse.2022.018102

Abstract It is a common observation that whenever patients arrives at the front desk of a hospital, outpatient clinic, or other health-associated centers, they have to first queue up in a line and wait to fill in their registration form to get admitted. The long waiting time without any status updates is the most common complaint, concerning health officials. In this paper, UrNext, a location-aware mobile-based solution using Bluetooth low-energy (BLE) technology is presented to solve the problem. Recently, a technology-oriented method, the Internet of Things (IoT), has been gaining popularity in helping to solve some of the healthcare sector’s problems.… More >

Mohanad Al-Ghobari¹, Amgad Muneer^2,*, Suliman Mohamed Fati³

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1553-1570, 2021, DOI:10.32604/cmc.2021.016348

Abstract Many tourists who travel to explore different cultures and cities worldwide aim to find the best tourist sites, accommodation, and food according to their interests. This objective makes it harder for tourists to decide and plan where to go and what to do. Aside from hiring a local guide, an option which is beyond most travelers’ budgets, the majority of sojourners nowadays use mobile devices to search for or recommend interesting sites on the basis of user reviews. Therefore, this work utilizes the prevalent recommender systems and mobile app technologies to overcome this issue. Accordingly, this study proposes location-aware personalized… More >