Quantifying Overfitting: Introducing the Overfitting Index

In the rapidly evolving domain of machine learning, ensuring model generalizability remains a quintessential challenge. Overfitting, where a model exhibits superior performance on training data but falters on unseen data, is a recurrent concern. This paper introduces the Overfitting Index (OI), a novel metric devised to quantitatively assess a model's tendency to overfit. Through extensive experiments on the Breast Ultrasound Images Dataset (BUS) and the MNIST dataset using architectures such as MobileNet, U-Net, ResNet, Darknet, and ViT-32, we illustrate the utility and discernment of the OI. Our results underscore the variable overfitting behaviors across architectures and highlight the mitigative impact of data augmentation, especially on smaller and more specialized datasets. The ViT-32's performance on MNIST further emphasizes the robustness of certain models and the dataset's comprehensive nature. By providing an objective lens to gauge overfitting, the OI offers a promising avenue to advance model optimization and ensure real-world efficacy

Open Kitchen

Poem by Sanad El-Rahaib

Identifying the Interrelationships of Critical Success Factors for Customer Relationship Management

An effective Customer Relationships Management (CRM) implementation benefits firms to achieve competitive advantages over others by enhancing customer retention, loyalty, satisfaction, and growing. A successful CRM implementation has become essential owing to the massive percentage of failures that occur. This year, firms are expected to spend more than $27 billion on implementing CRM. While a significant amount of study has been conducted into CRM implementations, particularly with respect to Critical Success Factors (CSFs), only a minority of the implementations have been successful. It is argued that one of the reasons for this is the improper assessment of interrelationships of CSFs prior starting the CRM implementation. CSFs are interlinked. They represent factors at nodes in a network of influences, which need to be examined together in order to determine best practice, identify study issues and reflect on strategy. Therefore, the aim of this study is to determine the interrelationships between the identified CSFs associated with CRM implementation, which revealed the important of these relationships for the success of the implementation. The study involves practical work based on one particular national context; the Kingdom of Saudi Arabia (KSA)

An explainable recommender system based on semantically-aware matrix factorization.

Collaborative Filtering techniques provide the ability to handle big and sparse data to predict the ratings for unseen items with high accuracy. Matrix factorization is an accurate collaborative filtering method used to predict user preferences. However, it is a black box system that recommends items to users without being able to explain why. This is due to the type of information these systems use to build models. Although rich in information, user ratings do not adequately satisfy the need for explanation in certain domains. White box systems, in contrast, can, by nature, easily generate explanations. However, their predictions are less accurate than sophisticated black box models. Recent research has demonstrated that explanations are an essential component in bringing the powerful predictions of big data and machine learning methods to a mass audience without a compromise in trust. Explanations can take a variety of formats, depending on the recommendation domain and the machine learning model used to make predictions. Semantic Web (SW) technologies have been exploited increasingly in recommender systems in recent years. The SW consists of knowledge graphs (KGs) providing valuable information that can help improve the performance of recommender systems. Yet KGs, have not been used to explain recommendations in black box systems. In this dissertation, we exploit the power of the SW to build new explainable recommender systems. We use the SW\u27s rich expressive power of linked data, along with structured information search and understanding tools to explain predictions. More specifically, we take advantage of semantic data to learn a semantically aware latent space of users and items in the matrix factorization model-learning process to build richer, explainable recommendation models. Our off-line and on-line evaluation experiments show that our approach achieves accurate prediction with the additional ability to explain recommendations, in comparison to baseline approaches. By fostering explainability, we hope that our work contributes to more transparent, ethical machine learning without sacrificing accuracy

Más allá del sueño de Burckhardt: La poesía de John Greenleaf Whittier

Using Said`s Orientalism, this paper investigates Whittier’s portrayal of Petra. In its discussion of Whittier’s representation of Petra, it examines how Eurocentric dialectics and Orientalism operate in his poetic consciousness. In particular, it analyzes the main traits of his Eurocentric discourse in “The Rock in El-Ghor.” It, moreover, argues that his textual treatment of Petra, to a great extent, emphasizes his faith in Western superiority in sharp contrast to Oriental inferiority. This paper concludes with a consideration of Whittier’s involvement in Petra as being, in one way or another, a token of what might be called IntraOrientalism. Usando el Orientalism de Said, este trabajo investiga la descripción de Petra hecha por Whittier. En sus discusiones sobre dicha representación de Petra, se examina cómo la dialéctica eurocéntrica y el orientalismo operan en su consciencia poética. Concretamente, analiza los principales rasgos de su discurso eurocéntrico en “in “The Rock in El-Ghor”. Además argumenta que su tratamiento textual de Petra, en gran medida, subraya su fe en la superioridad occidental en marcado contraste con la inferioridad oriental. Este trabajo concluye considerando que la implicación de Whittier en Petra, de una u otra manera, es una muestra de lo que podría denominarse el intra-orientalismo

U.Dream goes to market - an evaluation of U.purpose as a business unit and analysis of the internal and external environments affecting its strategic position

U. Dream is a social enterprise targeted at developing social leadership skills. It recently launched U. Purpose(service)and Crescer com Consciência (product) aiming to ensure future financial sustainability. However, these were launched without conducting a market research and clear guiding strategy. The focus of this project is to assess the attractiveness of the CSR and children’s book markets and U. Dream’s current strategy, providing a strategic revision. Analysis highlighted the attractiveness of the market. In Portugal, the CSR consulting market is considerably underdeveloped and is expected to grow on the foreseeable future, which gives U. Dream the opportunity to earn a first mover advantage. Nevertheless, it was underlined that U. Purpose has significant improvements to implement before launching, namely, to develop an extensive marketing strategy and a dedicated U. Purpose team

Could different Items arrangements affect 10th grade students' performance in multiple-choice tests in Maths, Science, and English language final exams

The present study investigated the effect of the order of the subjects and tests of mathematics, science and English language tests on the performance and achievement of the tenth grade students in Jordan. The study sample consisted of 764 students selected from twenty regular government schools. The study adopted quasi-experimental design. The study instrument used was a multi-choice type of 48 subjects for mathematics, science and English. The test items were arranged according to their difficulty for three processors (RDM), Easy -to-Hard (ETH) and Hard-to-Easy (THE). The data collected were analyzed statistically using the analysis of mono-variance at the statistical significance level of 0.01. The results of the analysis indicated that for mathematics, science and English courses, and in the order of items, the change in performance was statistically and morally significant, and it was found that the proposal to rearrange the test items for final achievement tests to control the penetration and misbehavior of the test rules and controls may not be optimal, The study of the English language, which did not show significant differences and suggests the use of other methods such as random model and parallel and split- half tests and further studies of other levels of study. Keywords: Multiple-choice, Item-position, Student Performanc

Investigating garment drape behaviour

Drapeability is one of the most important visual properties affecting garment appearance. Even though there are many studies concerned with fabric drape, understanding about the drape behaviour of garments is very limited. This study analyzes the key properties affecting the drape behaviour of garments to provide prediction equations. Results are statistically analyzed. From multiple regression analysis, drape rank scores obtained from subjective analyses are predicted using weight, bending modulus and extensibility measured at 100 gf/cm with a correlation coefficient of 0.94. Ranking values obtained from subjective analyses can be more easily predicted using both circularity and wave length minimum. A new equation was derived to predict drape rank score values of garments (correlation coefficient r = 0.97) depending on circularity and wavelength minimum

An Ensemble Approach to Question Classification: Integrating Electra Transformer, GloVe, and LSTM

This paper introduces a novel ensemble approach for question classification using state-of-the-art models -- Electra, GloVe, and LSTM. The proposed model is trained and evaluated on the TREC dataset, a well-established benchmark for question classification tasks. The ensemble model combines the strengths of Electra, a transformer-based model for language understanding, GloVe, a global vectors for word representation, and LSTM, a recurrent neural network variant, providing a robust and efficient solution for question classification. Extensive experiments were carried out to compare the performance of the proposed ensemble approach with other cutting-edge models, such as BERT, RoBERTa, and DistilBERT. Our results demonstrate that the ensemble model outperforms these models across all evaluation metrics, achieving an accuracy of 0.8 on the test set. These findings underscore the effectiveness of the ensemble approach in enhancing the performance of question classification tasks, and invite further exploration of ensemble methods in natural language processing

“El encuentro de dos mitades: ‘The City of Brass’ de Rudyard Kipling

This essay by and large revises the historically acknowledged notion that Kipling is an Indian-influenced author as postcolonial reassessments of Kipling's oeuvre have tended to focus primarily on Kipling’s relationship with the British Empire and India. In drawing on Intertextuality, Historicism, Said’s Orientalism, and Bhabha’s ambivalence, the essay analyzes Kipling’s poem in terms of its historical context, textual relationships with an Arabic narrative, and Kipling’s Orientalism. On the whole, this essay examines Kipling’s appropriation of a narrative from The Arabian Nights. The essay sheds light on Kipling’s preoccupation with an Arabic text– a preoccupation that can be interpreted as symptomatic of Kipling’s textual, ambivalent Orientalism. The Arabic narrative of the City of Brass, which enriches Kipling’s poem lexically and thematically, seems to be Kipling’s palimpsest upon which he writes his poem. Kipling’s drawing on the Arabic story by copying the title and the epigraph uncovers an unnoticed (not merely textual) relationship between Edward Lane (whose Orientalism is typical of Kipling’s “The White Man’s Burden”) and Kipling. This textual mixture between a postcolonial poem and a colonized narrative offers deep insights into Kipling’s ambivalence toward his White Men, who have been responsible for making Great Britain similar to the City of Brass in the original narrative