The relationship between the Nigerian police and citizens is strained, hindering the co-design of conventional technologies to enhance community policing (CP) initiatives, hence the imperative to involve both in the design of a usable CP technology that can carter for their needs.Our preliminary findings indicate that Nigerian citizens are reluctant to participate in co-design activities with the police due to discomfort and fear, which could potentially bias the design outcomes.Designing a CP technology with such stakeholders is crucial, but a new challenge for the Human Computer Interaction (HCI) community, as no existing framework has addressed it.We introduce Conflict Sensitive Design (CSD), a co-design approach that leverages mediation techniques (tension reduction, leveling, common ground reminder, separated meetings, formalizing agreements) to iteratively collect, analyze, and reconcile design inputs, ensuring that the final design is usable for CP enhancement.Our case application worked in CP technology requirements gathering with Nigerian CP stakeholders, and it could be extended to related HCI contexts.We present a structured approach to conflict resolution in co-design processes, and discuss the lessons learned as a spotlight to guide other designers in related contexts.

The concept of Federated Learning (FL) is a distributed-based machine learning (ML) approach that trains its model using edge devices. Its focus is on maintaining privacy by transmitting gradient updates along with users' learning parameters to the global server in the process of training as well as preserving the integrity of data on the user-end of internet of medical things (IoMT) devices. Instead of a direct use of user data, the training which is performed on the global server is done on the parameters while the model modification is performed locally on IoMT devices. But the major drawback of this federated learning approach is its inability to preserve user privacy complete thereby resulting in gradients leakage. Thus, this study first presents a summary of the process of learning and further proposes a new approach for federated medical recommender system which employs the use of homomorphic cryptography to ensure a more privacy-preservation of user gradients during recommendations. The experimental results indicate an insignificant decrease with respect to the metrics of accuracy, however, a greater percentage of user-privacy is achieved. Further analysis also shows that performing computations on encrypted gradients at the global server scarcely has any impact on the output of the recommendation while guaranteeing a supplementary secure channel for transmitting user-based gradients back and forth the global server. The result of this analysis indicates that the performance of federated stochastic modification minimized gradient (FSMMG) algorithm is greatly increased at every given increase in the number of users and a good convergence is achieved as well. Also, experiments indicate that when compared against other existing techniques, the proposed FSMMG outperforms at 98.3% encryption accuracy.

In recent times, many studies have identified trust as a propeller of community policing for enhancing security and safety. However, this essential aspect of community policing has not been properly classified. This has resulted in ambiguity and misunderstanding of the trust being referred to in community policing context. To cover this gap, this research carried out a systematic review of three scientific journal databases using PRISMA protocol which produced 16 document results after excluding 20,270 studies that didn't meet our criteria. Consequently, community policing trusts were identified and categorized in terms of technology-based trust (TbT), Human-to-Human Trust (HtHT) and Trust for both humans and technology (TbHT). Also, the research further established three themes for improving trust in community policing. In the end, this study has established the significant effect of different categories of trust as it supports community policing. More so, while this research informs on work that has been done on trust and community policing overtime, it provides distinct and comparable terms for future Human Computer Interaction (HCI) research.