Implementing a Chatbot Music Recommender System Based on User Emotion

The use of chatbots has become increasingly popular in recent years, as more organisations try to improve and streamline their customer service operations. One area which has been gaining momentum is the use of chatbots for music recommendation. Such systems utilise AI technologies to deliver personalised music recommendations to users via conversational interfaces. Chatbot music recommender systems present several benefits namely; they provide a personalised and natural experience which can be engaging for the users. Moreover, the users can engage in a dialogue whereby the system can better interpret the user context and preferences. This work presents the development of a chatbot personalised music recommender system, based on Natural Language Processing (NLP) techniques, coupled with a web interface that can provide song recommendations based on the user’s emotions

Real-Time Customer Emotion Analysis in E-Commerce based on Social Media Data: Insights and Opportunities

In this era of social media, it's essential for businesses to monitor their customers options and feelings regarding their services and products in a timely manner. Due to the ease of sharing opinions and feedback on social media, the customers can share their reviews about the business or a product instantly. This feedback can have a significant impact on the business's reputation and in turn on its revenue. In this regard, sentiment analysis has developed into a vital tool that companies can use to comprehend the emotional factors that influence client behavior and to aid them in making decisions that will increase customer pleasure. This work presents the use of social media data for real-time consumer emotion analysis in e-commerce. The study aims to identify the most expressed emotions and provide businesses with the ability to tailor their product and services accordingly. The employed dataset consists of 58,000 English comments that have been labelled for 27 different emotion categories. The study uses machine learning methods to categorize the emotions expressed in the comments, including convolutional neural networks and Bidirectional Encoder Representations from Transformers (BERT). The practical result of this research shows the importance of machine learning model coupled with a user interface that can provide stakeholders, such as e-commerce companies, with insights into consumer emotion as well as realtime customer sentiment about their goods and services

Increasing the simulation performance of large-scale evacuations using parallel computing techniques based on domain decomposition

Evacuation simulation has the potential to be used as part of a decision support system during large-scale incidents to provide advice to incident commanders. To be viable in these applications, it is essential that the simulation can run many times faster than real time. Parallel processing is a method of reducing run times for very large computational simulations by distributing the workload amongst a number of processors. This paper presents the development of a parallel version of the rule based evacuation simulation software buildingEXODUS using domain decomposition. Four Case Studies (CS) were tested using a cluster, consisting of 10 Intel Core 2 Duo (dual core) 3.16 GHz CPUs. CS-1 involved an idealised large geometry, with 20 exits, intended to illustrate the peak computational speed up performance of the parallel implementation, the population consisted of 100,000 agents; the peak computational speedup (PCS) was 14.6 and the peak real-time speedup (PRTS) was 4.0. CS-2 was a long area with a single exit area with a population of 100,000 agents; the PCS was 13.2 and the PRTS was 17.2. CS-3 was a 50 storey high rise building with a population of 8000/16,000 agents; the PCS was 2.48/4.49 and the PRTS was 17.9/12.9. CS-4 is a large realistic urban area with 60,000/120,000 agents; the PCS was 5.3/6.89 and the PRTS was 5.31/3.0. This type of computational performance opens evacuation simulation to a range of new innovative application areas such as real-time incident support, dynamic signage in smart buildings and virtual training environments

Applicability of Federated Learning for Securing Critical Energy Infrastructures

Energy grids are becoming more intelligent due to the use of a vast array of technologies, including the Internet of Things and Intelligent Systems. These Critical Energy Infrastructures, which are essentially cyber-physical systems, are particularly vulnerable to cyber threats. Machine Learning (ML) techniques have been increasingly used in security applications, and the energy domain is no exception. One approach, in particular, Federated Learning (FL), employs a distributed architecture and has potential in security applications, as it counters the issue of having a centralized data warehouse. In this work, a review of FL and its applications in security and privacy are presented. Moreover, a demonstration case involving a simulated model of FL for enhancing the security of systems is implemented and discussed. This demonstration case has provided added insight into potential issues and challenges as well as mitigation strategies

A Comprehensive Review of Mobile User Interfaces in mHealth applications for elderly and the related ageing barriers

Purpose: The adoption of mobile health technology can assist in enhancing the quality of life of elderly people. Over the last few years, though mHealth research has expanded, the usage of mHealth applications among elderly is still minimal. This study aims to evaluate mobile User Interfaces in mHealth applications and elicit the key ageing barriers that limit the use of such apps amongst the elderly. Methods: The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) technique was used whereby 28 papers were identified and examined out of 742. In addition to the systematic review, an experiment of using 5 existing mHealth apps, was conducted with 10 individuals within the age-group of 60-79 to determine additional ageing barriers and usage challenges. The Questionnaire for User Interface Satisfaction (QUIS) approach was used to prepare a questionnaire to assess the overall system satisfaction and was provided to participants after one week of usage. Results: In this work, issues with the user interface that impact the elderly have been highlighted. Three important ageing barriers hindering the use of mHealth among the elderly have been identified via PRISMA, namely: physical, cognitive and perspective. Empirical findings from the experiment carried out further consolidate the findings obtained from the PRISMA approach. Conclusion: This study's investigation emphasised on the performance of older persons with mHealth apps, their needs, and the challenges they confront when adopting mHealth technologies. As a result, technology designers will benefit from this information when developing and designing mHealth apps and services that are suitable for older adults

An ICT architecture for Smart Local Councils: a Mauritian case study

The purpose of this paper is to present the work done with regards to the development of an ICT architecture for Smart Local Councils in Mauritius (SLCs). This is in line with vision of the Mauritian government to convert the Mauritius into a Smart Island. Local councils play an important role in the delivery of services to citizen and their conversion to Smart Local Councils will contribute to the transformation of the island. The methodology used to develop the ICT architecture is presented. The components for each layer, based on architecture principles are discussed. The validation which include, validation against the architecture principles, validation through stakeholders’ focus groups and also validation in terms of its contribution to smartness are discussed. This paper provides added value as it shows how the gaps for converting Mauritian local councils into SLCs can be addressed through the proposed architecture. It provides the main building blocks which can aid in designing the roadmap for ICT architecture for Mauritian SLCs