10th International Congress on Information and Communication Technology in concurrent with ICT Excellence Awards (ICICT 2025) will be held at London, United Kingdom | February 18 - 21 2025.
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Authors - Welekazi Ntloko, Sara S. (Saartjie) Grobbelaar Abstract - Social franchising is a business model in which a successful social enterprise is replicated in multiple areas, often by providing franchisees with training, support, and resources. Social franchising aims to assist social entrepreneurs to impact a larger number of people with their services by scaling their operations while maintaining their standards of excellence and consistency. Social franchising (SF) is used to scale social business models in new locations, allowing them to expand their impact. This article serves to analyse and review the literature surrounding social franchising. Preliminary results reveal a substantial focus on healthcare in social franchising research, with limited multidisciplinary studies. Challenges include the limited legal frameworks in many jurisdictions, impacting stakeholder certainty. The study aims to contribute insights into the evolving landscape of social franchising, emphasizing the intersection with SBMs and HO for sustainable and impactful outcomes, with potential implications for sustainable economic and social development.
Authors - Kuhlula Mathebula, Noluntu Mpekoa, Khutso Lebea Abstract - This research aims to assess the suitability of a multi-factor authentication (MFA) scheme for protecting a university's Wi-Fi network from threat actors. Given the vulnerabilities of current single-factor authentication methods, which often rely on usernames and passwords, implementing MFA is proposed as a more secure alternative. MFA enhances security by requiring users to pass through multiple authentication mechanisms, such as knowledge-based, possession-based, and biometric methods, making unauthorised access significantly more difficult. The research seeks to determine the most effective combination of authentication factors for a university environment. The research findings may have broader implications for securing educational institutions' networks.
Authors - Amr Abu Alhaj, Omar Safwat, Youssef Ghoneim, Imran Zualkernan, Ali Reza Sajun Abstract - This paper examines the use of pre-trained models like Bidirectional Encoder Representations from Transformers (BERT) and A Robustly Optimized BERT Pretraining Approach (RoBERTa) to create reliable models for detecting fake news from media articles. Traditional Machine Learning (ML) methods frequently have difficulties in accurately identifying the nuances of misinformation due to extensive feature engineering dependencies. The latest advancements in Large Language Models (LLMs) such as BERT and RoBERTa have fundamentally transformed misinformation detection by providing deep context. The research utilizes the LIAR dataset, containing 12.8k manually labeled statements from PolitiFact.com, along with associated metadata and speaker credit scores. The approach combines BERT/RoBERTa embeddings with complementary architectures for binary classification, introducing a credit-score calculation reflecting speakers’ historical truthfulness. Notably, BERT-BiLSTM-CNN-FC and RoBERTa-BiLSTM-CNNFC configurations achieved state-of-the-art F1-scores of 0.76 and 0.74, respectively.
Authors - Ana Martinez-Gamez, Heberto Ferreira-Medina, Bernardo Lopez-Sosa, Sayra Orozco, Mario Morales-Maximo, Carlos A. Garcia, Michel Rivero Abstract - This project aims to develop a methodology for predicting solar radiation in San Francisco Pich´ataro, a community in the municipality of Tingambato, Michoac´an, Mexico. This community lies within the Pur´epecha indigenous zone. The project utilized two databases: one from a solarimetric station in the area and the other from the Solcast platform, which provides access to solar irradiance and other pertinent meteorological variables. Rigorous data cleansing and analysis procedures were implemented to ensure data quality and compatibility. Subsequently, both linear and decision tree regression models were applied to the refined and prepared data to forecast solar radiation.
Authors - Haryadi Sarjono, Safina Alya Zahira, Ine Silviya, Boyke Setiawan Soertin Abstract - This study aims to identify the office layout that best suits Gen Z workers' preferences and enhances productivity and work quality. A qualitative method with a descriptive approach was employed, focusing on Gen Z employees in the Information and Technology Division. Among the 38 employees in this division, ten are Gen Z, and eight of them participated in the study through a questionnaire and partial interviews to delve deeper into their responses. The questionnaire covered six different office layout types and assessed their impact on work productivity and efficiency. Gen Z employees in the Information and Technology Division favored new layouts, particularly the Relax Corner, Desk Facing Outside Window, Mini Bar, and WFO Feel Like WFC. They prefer cozy, flexible office spaces with diverse work environments. The findings suggest that these new office layouts can enhance productivity and work efficiency for Gen Z employees. However, some participants noted that their productivity and efficiency were more influenced by factors like their colleagues and teamwork rather than the office layout itself.
Authors - Rolph Abraham YAO, Ferdinand Tonguim GUINKO Abstract - Software-defined networking (SDN) is a growing concept that allows the separation of the control layer from the data layer, making the network programmable, and having a centralized view and management of the network. The control layer is an important component of the network because it is composed of controllers that play a role in supervising and controlling the entire SDN network. For efficient traffic management in SDN, it is essential to have a high-performance controller. In this paper, a performance analysis of Floodlight, ONOS, OpenDaylight (ODL) and Ryu controllers is analyzed. A custom network topology is created with Mininet. The ping and iperf tools are also used to evaluate the four controllers based on bandwidth utilization, jitter, packet transmission rate, round-trip time (rtt), and throughput. Our analysis reveals that in terms of jitter, bandwidth utilization, and throughput, ONOS has the best performance. Floodlight has better performance in terms of round-trip time (rtt) and ODL provides better performance in terms of transmission rate.
