This work demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were shown to demonstrate model generality over (...) the video temporal dimension. Predicted captions were shown to generalize over video action, even in instances where the video scene changed dramatically. Model architecture changes are discussed to improve sentence grammar and correctness. (shrink)

This paper illustrates the significance of the epistolary short story within the cultural backgrounds of the various settings in the stories selected for the study. The short stories deployed in this essay are Karen King-Aribisala’s ‘Dear Okonkwo,’ Dul Johnson’s ‘Cinders of the Volcano,’ Kasimma Chinelo Okani’s ‘A Letter to the Dead,’ and Chuma Nwokolo’s ‘The Ransom Letters of Sisi Eko.’ The methodology adopted in this study is textual and qualitative deployed through an in-depth study of the selected stories and a (...) literary analysis of the data obtained thereafter. This study adopts the new formalism critical approach with the belief that literature should be studied as a combination of the artistic content and the society that produces it. This essay finds that the Nigerian epistolary short story is significant in the promotion and enablement of necromancy, provision of emotional and psychological therapy and promotion of moral rectitude in the society. (shrink)

Unless and until our society recognizes cyber bullying for what it is, the suffering of thousands of silent victims will continue.” ~ Anna Maria Chavez. There had been series of research on cyber bullying which are unable to provide reliable solution to cyber bullying. In this research work, we were able to provide a permanent solution to this by developing a model capable of detecting and intercepting bullying incoming and outgoing messages with 92% accuracy. We also developed a chatbot automation (...) messaging system to test our model leading to the development of Artificial Intelligence powered anti-cyber bullying system using machine learning algorithm of Multinomial Naïve Bayes (MNB) and optimized linear Support Vector Machine(SVM). Our model is able to detect and intercept bullying outgoing and incoming bullying messages and take immediate action. (shrink)

Libraries provide resources for knowledge acquisition, recreation, personal interests and inter-personal relationships for all categories of users. It enables the individual to obtain spiritual, inspirational, and recreational activities through reading, and therefore the opportunity of interacting with the society’s wealth and accumulated knowledge. This study examined the undergraduate students’ use of University library services and resources. It was affirmed the undergraduate utilized the University Libraries as learning centre. This was shown by the massive turn out to patronize the library services (...) and resources weekly. (shrink)

In this research, we focus on the usage of adversarial sampling to test for the fairness in the prediction of deep neural network model across different classes of image in a given dataset. While several framework had been proposed to ensure robustness of machine learning model against adversarial attack, some of which includes adversarial training algorithm. There is still the pitfall that adversarial training algorithm tends to cause disparity in accuracy and robustness among different group. Our research is aimed at (...) using adversarial sampling to test for fairness in the prediction of deep neural network model across different classes or categories of image in a given dataset. We successfully demonstrated a new method of ensuring fairness across various group of input in deep neural network classifier. We trained our neural network model on the original image, and without training our model on the perturbed or attacked image. When we feed the adversarial samplings to our model, it was able to predict the original category/ class of the image the adversarial sample belongs to. We also introduced and used the separation of concern concept from software engineering whereby there is an additional standalone filter layer that filters perturbed image by heavily removing the noise or attack before automatically passing it to the network for classification, we were able to have accuracy of 93.3%. Cifar-10 dataset have ten categories of dataset, and so, in order to account for fairness, we applied our hypothesis across each categories of dataset and were able to get a consistent result and accuracy. (shrink)

This paper examines the narrative techniques; setting, focalization and flashback, employed by Adekunle Mamudu and Sophia Akhuemokhan in The Beauty of Madness and Changing Colors respectively, to arouse deep meanings and intense emotions. These techniques contribute to the message the writers intend to pass across to the readers. While Akhuemokhan uses these techniques in Changing Colors to teach morals and promote ethnic principles, Mamudu’s aim in The Beauty of Madness is to expose some ills revolving in the society and (...) launch sanity back to the society. (shrink)