This study sets out to assess Micro Finance Banks' activities and SMEs Supply Chain Finance in the Federal Capital Territory(FCT), with the twin objectives of assessing if Micro Finance Banks activities in the FCT meets the supply chain obligations of SMEs and to determine whether the growth and survival of SMEs in the FCT are independent of the activities of Micro Finance Banks. The methodology adopted for the study is descriptive survey design and at the end, the study found that, MFBs activities have a negative relationship with SMEs supply chain finance meaning; the activities of Micro Finance Banks are not related to SMEs meeting their supply chain obligations in the FCT, Abuja. While on the other hand, it is found MFBs activities has positive relationship with the growth and survival of SMEs, meaning; the activities of Micro Finance Banks are not independent of the growth and survival of SMEs in FCT. It is therefore recommended that; the Federal Government/CBN should direct MFBs to prioritise SCF services to SMEs sector, lower interest rates to single digit, and ensure adequate monitoring on intervention initiatives, while SMEs should also acquire relevant business skills.

Songs perform key roles in the society such as entertainment and education but can project certain ideologies and stereotypes. This study examined the objectification of women in selected Kipsigis popular songs. The researcher purposively picked 15 songs from speakers of Kipsigis popular artists, 30 respondents and five composers. An interview schedule was used to obtain the relevant information from the respondents and composers of the songs. The study was guided by Politeness Theory by Brown and Levinson (1978). The results of the study indicated that artists objectify women as instruments, female sex organ as food and a place while sexual intercourse is portrayed as a journey, war and work to mitigate their offensiveness. It is believed that the findings of this study would be of great significance in information dissemination to the media, schools and churches in censuring and sensitization of songs that objectify women. Also, the results of this study is expected to be instrumental in mitigating offensive expressions that cause harm and shame to the listeners of Kipsigis popular songs through proper interpretation of words and phrases that objectify women.

In this paper, we discussed about the several machine learning algorithms and its use in recognition of human activity .Human activity recognition is an active field of research today that aims to understand human behavior by interpreting sensory information collected from humans and their living environment. Machine learning is an evolving branch of the computational algorithms that are designed to find the human intelligence by learning from the surrounding existing environment and it considered the working horse in the new era of the so-called big data also. The techniques based on machine learning have been applied successfully in diverse fields ranging from pattern recognition, computer vision as well on spacecraft engineering, finance, entertainment, and computational biology to biomedical and medical applications. These are few types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. Machine learning have neural networks like ANN, RNN, CNN and algorithms classifier like first is Linear Models, Logistic Regression, Support Vector Machines.second is Non-linear Models. K-Nearest Neighbours. Kernel SVM. Naïve Bayes, Decision Tree Classification, Random Forest Classification. This paper shows the technology analysis of some recent existing human activity recognition techniques using different algorithm and neural networks. At end of this review paper compared results show the accuracy parameter of different algorithms.