Search results for: Jamaluddin Othman

Authors: Muhammad Abu-Khaizaran, Ahmad Faza’, Tariq Othman, Yahia Yousef

Abstract:

This paper presents a study to provide sufficient and reliable information about constructing a Photovoltaic energy profile of the Birzeit University campus (BZU) based on the weather forecast. The developed Photovoltaic energy profile helps to predict the energy yield of the Photovoltaic systems based on the weather forecast and hence helps planning energy production and consumption. Two models will be developed in this paper; a Clear Sky Irradiance model and a Cloud-Cover Radiation model to predict the irradiance for a clear sky day and a cloudy day, respectively. The adopted procedure for developing such models takes into consideration two levels of abstraction. First, irradiance and weather data were acquired by a sensory (measurement) system installed on the rooftop of the Information Technology College building at Birzeit University campus. Second, power readings of a fully operational 51kW commercial Photovoltaic system installed in the University at the rooftop of the adjacent College of Pharmacy-Nursing and Health Professions building are used to validate the output of a simulation model and to help refine its structure. Based on a comparison between a mathematical model, which calculates Clear Sky Irradiance for the University location and two sets of accumulated measured data, it is found that the simulation system offers an accurate resemblance to the installed PV power station on clear sky days. However, these comparisons show a divergence between the expected energy yield and actual energy yield in extreme weather conditions, including clouding and soiling effects. Therefore, a more accurate prediction model for irradiance that takes into consideration weather factors, such as relative humidity and cloudiness, which affect irradiance, was developed; Cloud-Cover Radiation Model (CRM). The equivalent mathematical formulas implement corrections to provide more accurate inputs to the simulation system. The results of the CRM show a very good match with the actual measured irradiance during a cloudy day. The developed Photovoltaic profile helps in predicting the output energy yield of the Photovoltaic system installed at the University campus based on the predicted weather conditions. The simulation and practical results for both models are in a very good match.

Keywords: clear-sky irradiance model, cloud-cover radiation model, photovoltaic, weather forecast

Procedia PDF Downloads 132

Authors: Md. Rafiul Biswas, Uzair Shah, Mohammad Alkayal, Zubair Shah, Othman Althawadi, Kamila Swart

Abstract:

Background: Social media platforms play a significant role in the mediated consumption of sport, especially so for sport mega-event. The characteristics of Twitter data (e.g., user mentions, retweets, likes, #hashtag) accumulate the users in one ground and spread information widely and quickly. Analysis of Twitter data can reflect the public attitudes, behavior, and sentiment toward a specific event on a larger scale than traditional surveys. Qatar is going to be the first Arab country to host the mega sports event FIFA World Cup 2022 (Q22). Qatar has hosted the FIFA Arab Cup 2021 (FAC21) to serve as a preparation for the mega-event. Objectives: This study investigates public sentiments and experiences about FAC21 and provides an insight to enhance the public experiences for the upcoming Q22. Method: FCA21-related tweets were downloaded using Twitter Academic research API between 01 October 2021 to 18 February 2022. Tweets were divided into three different periods: before T1 (01 Oct 2021 to 29 Nov 2021), during T2 (30 Nov 2021 -18 Dec 2021), and after the FAC21 T3 (19 Dec 2021-18 Feb 2022). The collected tweets were preprocessed in several steps to prepare for analysis; (1) removed duplicate and retweets, (2) removed emojis, punctuation, and stop words (3) normalized tweets using word lemmatization. Then, rule-based classification was applied to remove irrelevant tweets. Next, the twitter-XLM-roBERTa-base model from Huggingface was applied to identify the sentiment in the tweets. Further, state-of-the-art BertTopic modeling will be applied to identify trending topics over different periods. Results: We downloaded 8,669,875 Tweets posted by 2728220 unique users in different languages. Of those, 819,813 unique English tweets were selected in this study. After splitting into three periods, 541630, 138876, and 139307 were from T1, T2, and T3, respectively. Most of the sentiments were neutral, around 60% in different periods. However, the rate of negative sentiment (23%) was high compared to positive sentiment (18%). The analysis indicates negative concerns about FAC21. Therefore, we will apply BerTopic to identify public concerns. This study will permit the investigation of people’s expectations before FAC21 (e.g., stadium, transportation, accommodation, visa, tickets, travel, and other facilities) and ascertain whether these were met. Moreover, it will highlight public expectations and concerns. The findings of this study can assist the event organizers in enhancing implementation plans for Q22. Furthermore, this study can support policymakers with aligning strategies and plans to leverage outstanding outcomes.

Keywords: FIFA Arab Cup, FIFA, Twitter, machine learning

Procedia PDF Downloads 100

Authors: Munqeth Othman Agha

Abstract:

The historical formation of urban centres in the eastern Arab world was shaped by rapid urbanization and sudden transformation from the age of the pre-industrial to a post-industrial economy, coupled with uneven development, informal urban expansion, and constant surges in unemployment and poverty rates. The city was stratified accordingly as overlapping layers of division and inequality that have been built on top of each other, creating complex horizontal and vertical divisions based on economic, social, political, and ethno-sectarian basis. This has been further exacerbated during the neoliberal era, which transferred the city into a sort of dual city that is inhabited by heterogeneous and often antagonistic social groups. Economic deprivation combined with a growing sense of marginalization and inequality across the city planted the seeds of political instability, outbreaking in 2011. Unlike other popular uprisings that occupy central squares, as in Egypt and Tunisia, the Syrian uprising in 2011 took place mainly within inner streets and neighborhood squares, mobilizing primarily on more or less upon the lines of stratification. This has emphasized the role of micro-urban and social settings in shaping mobilization and resistance tactics, which necessitates us to understand the way the city was stratified and place it at the center of the city-conflict nexus analysis. This research aims to understand to what extent pre-conflict urban stratification lines played a role in determining the different trajectories of three cities’ neighborhoods (Homs, Dara’a and Deir-ez-Zor). The main argument of the paper is that the way the Syrian city has been stratified creates various social groups within the city who have enjoyed different levels of accessibility to life chances, material resources and social statuses. This determines their relationship with other social groups in the city and, more importantly, their relationship with the state. The advent of a political opportunity will be depicted differently across the city’s different social groups according to their perceived interests and threats, which consequently leads to either political mobilization or demobilization. Several factors, including the type of social structures, built environment, and state response, determine the ability of social actors to transfer the repertoire of contention to collective action or transfer from social actors to political actors. The research uses urban stratification lines as the basis for understanding the different patterns of political upheavals in urban areas while explaining why neighborhoods with different social and urban environment settings had different abilities and capacities to mobilize, resist state repression and then descend into a military conflict. It particularly traces the transformation from social groups to social actors and political actors by applying the Explaining-outcome Process-Tracing method to depict the causal mechanisms that led to including or excluding different neighborhoods from each stage of the uprising, namely mobilization (M1), response (M2), and control (M3).

Keywords: urban stratification, syrian conflict, social movement, process tracing, divided city

Procedia PDF Downloads 73