Landmark University

Vehicle-to-vehicle (V2V) communication is a key component of intelligent transportation systems (ITS), enabling seamless data exchange between vehicles to limit collision risks. This study presents a hybrid communication framework that integrates light fidelity (LiFi) and wireless fidelity (WiFi) technologies to enhance safety and reliability in accident prevention. Lifi using visible light communication, provides line-of-sight for short-range communication, while WiFi ensures long-range coverage in dynamic traffic environments. The proposed system allows vehicles to share speed, braking, and positional data, enabling timely warnings to drivers in high-risk scenarios. The system fuses data communication protocol design, simulation, prototype development, testing, and evaluation. The prototype model was designed and simulated to evaluate the performance of the system in terms of functionality, timing and reliability. Results indicate that the hybrid LiFi-WiFi system improves data transmission efficiency and reduces delay compared to standalone wireless systems. This approach demonstrates significant potential in developing safer transportation networks by combining complementary wireless technologies for V2V communication.

Welding is a widely used and effective method of joining metals. However, serious challenges are often encountered in the process due to welding distortion. Distortions result from the thermal expansion and shrinkage of metals during the welding process. This review paper focuses on the mechanisms associated with welding distortion and various mitigation techniques adaptable by fabrication industries. Whereas full prevention of distortion is unattainable with a finite geometric accuracy, it can essentially be controlled to minimize the undesired impact of distortion on the geometric integrity, hence increasing the manufacturing efficiency and decreasing the production cost. This paper categorizes distortions into out-of-plane and in-plane deformation modes and describes the factors which influence distortions - welding parameters, sequences, and material properties. Furthermore, a review of traditional and novel mitigation strategies, such as the optimization of welding parameters and improved determination and prediction of the welding sequence schedule. In this review, based on the synthesis of current publications, efforts have been made to guide fabrication industries in determining appropriate procedures and parameters to be selected according to job requirements, with the sole aim of offering better weld quality and lowering of manufacturing cost.

The online version contains supplementary material available at 10.1007/s40203-026-00557-z.

This study examined the relationship between social media peer communication and perception, knowledge, and attitude toward cervical cancer prevention among female youth aged 15 to 29years in Kwara State, Nigeria. Anchored in the Health Belief Model, the study also investigated how youth engagement with posts on cervical cancer and Human Papillomavirus (HPV) influences their attitude about the vaccine. A quantitative cross-sectional survey was conducted among 379 female youth selected through a multi-stage stratified sampling technique from two public universities. Findings revealed a significant positive association between social media peer communication and cues to action, knowledge and perceived susceptibility, but vaccine uptake remains low (27.2%) due to stigma rooted in social perception that associates cervical cancer and HPV vaccine with sexual activity. These findings reinforce that awareness and knowledge of the HPV vaccine alone are insufficient in drivinguptake.Publichealthcampaignsshouldintegratesocialmediapeerdrivencommunications and peer influencer models that extend awareness and knowledge building to address social perceptions and stigma in their campaign efforts. Also, strategic peer advocacy can significantly complement traditional health education, creating a space where youth can learn directly from immediate peers, connect with like-minded individuals, and influence one another's attitudes towards a positive perception of the disease and vaccine uptake. Also, campaign messages should model HPV vaccination as socially acceptable, responsible and safe.

The article explores the perceptions and participation of undergraduates in practical agriculture education in Landmark University, Nigeria, and hypothesises whether the constraints associated with participation are significantly related to the perceived value of practical agriculture by students. Primary data were gathered using a structured questionnaire and analysed using descriptive statistics and exploratory factor analysis (PCA with oblimin rotation) on 329 undergraduates in four colleges. The respondents indicated positive involvement in practical agriculture and a positive attitude towards practical agriculture, with the highest scores on hands-on experience, acquisition of entrepreneurial skills, and perceived employment opportunities in the agricultural sector. Factor analysis produced five consistent elements, including perceived career value/ personal relevance, institutional resourcing and technology deficits, mentorship/ instructional support gaps, academic workload/time constraints, and status/aspiration misfit, explaining 62.55 per cent of total variance (KMO = 0.809; Bartlett’s χ² significant). The results indicate that to enhance practical agriculture performance, it is necessary to protect practical time, strengthen instructional and mentorship support, and increase integration of resources and technology to maintain student engagement and align practical agriculture with diverse aspirations.

Micronutrient deficiencies, also known as “hidden hunger,” remain a pervasive public health issue in low- and middle-income countries, particularly among vulnerable populations within these countries. The main drivers of these deficiencies are poverty, limited dietary diversity, weak nutritional strategies, poor health service delivery and general health access barriers. This review assesses the prevalence, drivers, and consequences of selected micronutrient deficiencies: iron, iodine, zinc, vitamin A and vitamin D, within the scope of undernutrition, food insecurity, and socioeconomic inequity. The consequences associated with these deficiencies include stunted growth, increased susceptibility to illness, poor cognitive and social functioning, and deepened poverty. The primary strategies to address these deficiencies include dietary diversification, supplement provision, biofortification, and the production of fortified foods. Barriers to progress include the high cost of food, weak healthcare infrastructure, low educational levels, and ineffective policy implementation. Integrated food systems, personalised nutrition, and innovative food technologies have the potential to address both nutritional and health inequities. Addressing barriers to safe and nutritious food and healthcare systems in order to address health inequities requires integrated, multisectoral planning and contextual policy. Improving individual health outcomes is crucial, but addressing micronutrient deficiencies has a ripple effect throughout society, enabling economic development through poverty reduction and increased productivity.

Network intrusion detection is a critical component of cybersecurity, as it ensures the integrity, confidentiality, and availability of networked systems. It plays a vital role in maintaining the security, and stability of modern network systems. This study presents a hybrid model combining Random Forest (RF) and Discrete Wavelength Transform (DWT) to enhance intrusion detection by leveraging the temporal features in the dataset of the network traffic. The RF algorithm was used in this study for its high classification accuracy and robustness the identification of complex patterns associated with intrusion. DWT’s capability for decomposing temporal traffic data, extracting meaningful features and isolating anomalies across multiple resolution levels was harnessed as well. Combining the Classification strength of RF and the feature extraction prowess of DWT, the model achieved improved detection accuracy and reduced false positive rates. This work highlights the potential of combining signal processing and machine learning techniques for robust network security solutions.