Graduate Journal of Interdisciplinary Research, Reports and Reviews
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The Double-Edged Sword of Artificial Intelligence in Academic Libraries and Research
No full textBackground: Artificial Intelligence (AI) which as described by Onwubiko is a replication of human intelligence planted in machines as the brain and programmed to think and act as human but powered by computer
Purpose: The study is an investigation into the beautiful and ugly sides of applications and utilization of artificial intelligence (AI) in Academic libraries and research.
Methods: It adopted a descriptive survey, while a Likert four point type structured questionnaire was the only instrument used for data collection. The instrument was validated by three experts in measurement and evaluation using Cronbach’s alpha. Result showed coefficient of α=.80. Data collected were analyzed using frequencies and simple percentile and presented in tables.
Result: The outcome of the study revealed among other things that application and use of AI in academic library will enhance service provision to users and can positively enhance academic research. While on the negative side, AI may not always provide accurate prediction or decision, depending on the complexity of the task and quality of data. With it, academic research, data security is not guaranteed that at a point in time. Also, researchers might start to think that AI knows everything and can replace human researchers among others.
Conclusion: Librarians and researchers agree that the application and utilization of AI will enhance library services and also enhance researchers’ scientific discovery and accelerates research process. Librarians in academic libraries in Nigeria should discard the allayed fears and view AI from the angle that it is a vital tool for the provision of vital information and enhancement of knowledge
A Comparative Study of Distance Metrics in Machine Learning for Credit Card Fraud Detection
Full text linkBackground: Credit card fraud detection is a critical problem due to the increasing volume of online transactions and the high costs associated with fraudulent activities. Previous studies in this field have investigated various machine-learning techniques to identify fraudulent transactions, with notable progress made through supervised learning methods. However, these models often face challenges due to the significant class imbalance in fraud detection datasets, where instances of fraud are much less frequent than legitimate transactions.
Purpose: As a result, there is growing interest in unsupervised techniques, such as clustering algorithms, which do not depend on labeled data and may offer improved generalization to new and unseen fraud patterns. These unsupervised approaches can autonomously identify anomalies by grouping transactions based on shared characteristics, making them a valuable alternative for detecting evolving fraudulent activities.
Methods: This work explores different distance metrics in clustering algorithms such as K-Means to identify fraudulent activity in a credit card dataset. The substantial class imbalance is highlighted by the European credit card transactions dataset, which consists of only 0.17\% of fraudulent transactions. The research utilizes multiple sampling techniques to address class imbalance.
Results: The study found that the Euclidean distance metric produced the best results out of all potential techniques when applied to the K-Means algorithm. It emphasizes how crucial it is to deal with class disparities and use unsupervised methods for fraud detection in practical settings.
Conclusions: In future research, there is scope for improvements in fraud detection systems, particularly in terms of finding enhanced algorithms and expanding data availability
A Study of Physio-chemical parameters for Binary Mixtures of Primary Alcohol/Bromoethane
No full textBackground: The binary liquid mixtures of methanol (MeOH) and bromoethane (BR) were analysed across the mixing range (0.0 to 1.0) to determine molecular interactions and structural properties at a constant temperature of 283 K.
Purpose: The ultrasonic speed and refractive index of the binary mixtures were measured at 283.15 K using a DMA 5000M (Anton Paar) and an Abbe refractometer, respectively.
Method: Acoustic parameters such as adiabatic compressibility (β), acoustic impedance (Z), and free length (Lf) were calculated from the ultrasonic velocity data of the binary mixtures. Some refractometric parameters, specifically internal pressure (Pint) and molecular radii (r), were assessed applying the measured refractive indices of binary mixtures.
Conclusions: The excess parameters of ultrasonic and refractometric properties were determined and fitted using R. K. polynomial analysis. All these determined parameters have been used to investigate heteromolecular interactions in molecular species. 
Forecasting Stock Market Prices through Long Short-Term Memory Method
Full text linkPrediction of futuristic price of stocks (shares) of listed companies at exchange has always been a fascinating area of interest for all kind of market participants. Whether short term traders. long term investors, or risk managers, everyone interest lies in forecasting the market accurately and in time. This study explores the application of Long Short-Term Memory (LSTM) networks, a class of Recurrent Neural Networks (RNNs), for predicting stock prices of major technology companies, Apple (AAPL), Google (GOOG), Microsoft (MSFT), and Amazon (AMZN) using historical data from 2005 to 2024. This work of mine “Stock Prediction using LSTM (Long Short-Term Memory”) method is a sincere effort in same direction, and I hope it will immensely help all market participants and serve them with more accuracy in forecasting share prices in near future period
Assessment of Wearing Resistant Property of the Fabricated Polymeric Ceramic Material
No full textBackground: A specific kind of substance in a polymeric material acts as a supporting framework, and the ceramic fragments enclosed within it are called a polymer-matrix ceramic composite. Due to the way distinct layers of composites attach to each other, the failure of composites varies from the characteristics of normal materials, and their efficacy is determined based on their wear-resistant properties.
Purpose: The aim of the study is to investigate the wear-resistant behaviors of commonly used composite materials.
Methods: Al2O3 and ZrO2 are the ceramic materials chosen for the investigation, while epoxy (formaldehyde and phenol) is the polymer chosen. By altering the weight proportion of the ceramics in the matrix of polymers, the study evaluates the outcomes of wear resistance.
Results: The results show that up to 30% of the time, the zirconia composites wore out more quickly than the alumina composites.
Conclusions: The study focuses on determining the wear-resistant behavior of zirconia and alumina composites, providing insights into their use in weight-sensitive applications
Design and Analysis of Universal Joint Center Block
Full text linkBackground: Universal joints are critical components in automotive power transmission systems, enabling torque transfer between misaligned shafts. One of the essential elements of this mechanism is the center block, which connects the driver and driven shafts and is subject to complex loading conditions.
Purpose: This study aims to analyze the structural performance of the center block by evaluating the effect of different material properties and design variations. The goal is to optimize the component in terms of strength, shape, size, and weight under real-time operating conditions.
Methods: Design and simulation tools including NX 12 and ANSYS Workbench 16 were used to create and analyze two center block designs. Fracture analysis was performed by applying appropriate moments while fixing other components to replicate realistic operational conditions. Four materials structural steel, stainless steel, aluminum alloy, and grey cast iron were tested in the simulation environment.
Results: The analysis revealed significant differences in performance based on material selection and design variation. Structural steel and stainless steel provided higher strength, while aluminum alloy offered considerable weight reduction. The optimized design demonstrated improved mechanical integrity and material efficiency.
Conclusions: Material selection and structural design significantly impact the mechanical behavior of the center block in a universal joint. Simulation-driven testing is effective in identifying optimal configurations, thereby enhancing the reliability and performance of automotive power transmission systems
The Mechanics of Inclined Honeycomb Structures: Advances and Challenges
No full textBackground: Inclined honeycomb structures have garnered significant attention due to their exceptional mechanical properties, including enhanced strength-to-weight ratios and improved energy absorption capabilities. These structures offer promising applications in aerospace, biomedical, and energy sectors.
Purpose: This comprehensive review aims to provide a deeper understanding of the complex mechanics governing inclined honeycomb structures. It sheds light on their mechanical properties, the effects of cell geometry and material properties, and the influence of inclined cell angles on their behavior.
Methods: Analytical and numerical models are reviewed to evaluate the impact of inclined cell angles on mechanical performance. Additionally, the study identifies optimal cell angles for enhanced mechanical properties, investigates stress distribution and failure mechanisms, and examines the role of cell wall thickness, material properties, and honeycomb configurations. Results: The findings reveal that inclined honeycomb structures exhibit improved mechanical properties compared to traditional honeycombs, including increased compressive strength and toughness. Variations in cell shape and design optimization strategies are also addressed, emphasizing the importance of geometrical parameters and material selection.
Conclusions: Despite their advantages, challenges such as manufacturing complexities and limited understanding of failure mechanisms remain. This review synthesizes existing knowledge, identifies research gaps, and outlines future research directions. By advancing research and overcoming these challenges, inclined honeycomb structures can be further optimized for high-performance applications in aerospace engineering, biomedical devices, energy absorption systems, automotive components, and advanced composite materials. This analysis will benefit researchers, engineers, and industry professionals in developing advanced inclined honeycomb structures
On Vertex-Based Dimension of Some Graphs Joining Certain Prism Graphs
Full text linkBackground: In graph theory, the prism graph is a type of graph that is characterised by having the structure of a prism as its underlying framework. The notion of a resolving set and that of metric dimension for a graph of a prism is important in uniquely identifying the vertices within a prism graph. For a non-trivial connected graph , an ordered subset of vertices any pair of different vertices , if for some . Such a set is said to be a resolving set for and the smallest cardinality of is called the of . Purpose: The purpose of this article is to determine the notion of resolving sets and their corresponding metric dimensions for two complex families of planar graphs obtained by joining copies of the prism graph on known families of convex polytope graphs.Methods: The methods used are purely theoretical, based on mathematical reasoning and established definitions related to graph theory.Results: In this article, we have determined successfully the resolving set and metric dimension for two specific complex families of planar graphs, denoted by and , constructed using copies of a prism graph. These findings contribute to our understanding of these concepts within graph theory.Conclusions: This research indicates the importance of studying resolving sets and metric dimensions in various graph structures, particularly those derived from multiple copies of the prism graph connected through known families of convex polytope graphs. This work may inspire further investigations into similar graph families or other applications of these concepts in different areas of mathematics and computer science.
Keywords: Metric dimension, independent set, basis set, convex polytope, prism graphs2000 Mathematics Subject Classification: 05C1
Scoping Review of Pressure Ulcer Prevalence and Prevention in Elderly Inpatient Care in England
No full textBackground: Treatment of pressure ulcer brings significant financial burden to NHS Commissioners in UK. Currently the prevalence of the issue shows a consistent yearly increase based on the research data.
Purpose: To evaluate the Pressure Ulcer Prevalence and Prevention on Care of the Elderly Inpatient Wards in England.
Methods: A scoping review was conducted to explore the available sources of information on the pressure ulcer prevalence and prevention specific to care of elderly wards in UK. This review is focussed on patients above the age of 65 and involves desk research.
Results: Inappropriate use and over-prescription of manual handling equipment, lack of timely risk assessment be the key reasons for increased prevalence of pressure ulcer cases in England. completion, education and training discrepancies, ineffective use of technology and specialist bedding were found to
Conclusions: The preliminary results conclude that, for the pressure ulcer prevention strategies to be effective, appropriate use of pressure relieving equipment and staff trainings on its use is imperative. Timely risk assessments are of utmost importance to reduce the cases of pressure ulcer in the care of elderly patient
Awareness of Drug and Substance Abuse Among Female Undergraduates: A Survey-Based Analysis
Full text linkBackground: Substance abuse is a significant public health issue, especially among young adults in higher education, due to distinct social, psychological, and biological factors. This study underscores the importance of addressing knowledge of substance abuse in educational settings, particularly among female students who face unique challenges and obstacles both in college and at home.
Purpose: This study aims to evaluate the knowledge and awareness of drug and substance abuse among undergraduate female students, highlighting the need for enhanced and targeted awareness initiatives.
Methods: A survey was administered to a sample of 948 female students enrolled in various graduate-level programs. Data were collected electronically using Google Forms and analyzed to assess the knowledge and awareness of drug and substance abuse among the participants.
Results: The findings reveal varying levels of awareness and knowledge regarding substance use among the respondents, with significant gaps identified. While some students recognize the importance of drug abuse education, there is a clear demand for more comprehensive and focused awareness programs. The literature review highlights which demands a motivation for change in substance abuse. global and regional trends in substance addiction, particularly the increased vulnerability of female students but the literature regarding knowledge among students is very less. In India, drug addiction among university students is influenced by factors such as peer influence, easy access to narcotics, isolation and sometimes academic pressure
Conclusions: This study provides insights into the understanding and awareness about the various forms of drug addiction in youth. By understanding their knowledge, perspectives, and experiences, educational institutions can develop more effective strategies to avoid substance abuse. To enhance knowledge about the negative impact of drug use and create a safer, healthier learning environment, addressing the motivation for substance use disorders is essential