Customer Shopping Pattern Prediction Using RNN (Recurrent Neural Network)

Spectrum of Engineering Sciences Journal | 2025

Customer relationship management is very important in making marketing decisions large amounts of customer transaction data in Point of Sales systems are helpful in predicting customer behavior. However, there are no better modelling methods to perform analysis on such large sets of data. Neural Networks are helpful in making better decisions for providing better marketing strategic plans. Large corporations should have huge quantities of data available to them to predict the possible potential purchasing behavior for many of their clients. That way they can make timely decisions about stocking their shelves, providing customer recommendations on items, customer promotions, and predicting when a customer is losing interest in their service and planning to buy from a competitor. This research proposes an experiment on a consumer behavior prediction model of buying products, utilizing recurrent neural networks (RNNs), focusing on client loyalty number, recency, frequency, monetary value, and introducing a novel variable termed clumpiness. According to the experimental evidence it was obtained that the RNN predicts RFMC for customers more efficiently and accurately than convectional RFM for the same cases. Recommendation systems can eventually use this model for target marketing in different segments. We provide a modelling strategy that can help to predict customers’ future long-term purchasing.

Analyzing the Impact of Smart Helmet Usage and Traffic Violations on Motorbike Accident Fatalities

AITU Scientific Research Journal | 2025

In recent years, where the use of motorbikes has increased due to its cost-effectiveness and reliability but also the surge in motorbike accidents is very alarming. A big portion of accident-related fatalities has been directly linked to body injuries including human body’s most sensitive part that is human’s head. Major reasons for fatalities involving head injuries by motorbike accidents includes not wearing helmets and violating traffic rules and regulations. To address this issue, this research presents an idea of a system consisting of a high-tech surveillance. The system uses advanced computer techniques including computer vision, image processing, and machine learning. The system runs a face detection and recognition module to identify and check helmet on the rider’s head. The aim of this research is to enhance the safety of rider by monitoring rider’s helmet, and motorbike’s speed in real-time. If any of these will be violated, then the system will launch a notification consisting of violated terms to their family. Furthermore, rider’s family can also watch rider through a live video feature. The system is evaluated and tested on a public dataset, and the obtained results showed that the system operates on high accuracy and efficiency.

Lightweight Cryptographic Algorithm Development Using Fundamental Cryptographic Techniques

VFAST Transactions on Software Engineering | 2025

Cryptography is used to make data and information transmission and computational systems secure over the networks by using mathematical and scientific techniques. The cryptographic algorithm should fulfil the conditions of authentication, confidentiality, integrity and reliability. In today’s era, where digital communication and data storage is increasing day by day and the data leakage, breaches and attacks are continuously rising. The increase in need of strong and secure cryptography algorithms to protect user information that ensures the integrity and confidentiality of data. The existing symmetric cryptographic algorithms like AES or DES, can provide strong security but they have very complex implementations and requires high computational resources. The aim of this paper is to provide a study for the research done in the field of cryptography, cryptographic techniques and to propose and developed a light weight symmetric cryptographic algorithm using different fundamental cryptographic techniques that is secure and fulfils the conditions of authentication, confidentiality, integrity and reliability.