Papers by Muhammad Sanwal
Toward Usable Formal Models for Safety and Performance Evaluation of ERTMS/ETCS Level 3: The PERFORMINGRAIL Project
Le Centre pour la Communication Scientifique Directe - HAL - memSIC, Aug 28, 2022
International Journal of Information Technology and Applied Sciences (IJITAS), 2021
In the current era, a rapid increase in data volume produces redundant information on the interne... more In the current era, a rapid increase in data volume produces redundant information on the internet. This predicts the appropriate items for users a great challenge in information systems. As a result, recommender systems have emerged in this decade to resolve such problems. Various e-commerce platforms such as Amazon and Netflix prefer using some decent systems to recommend their items to users. In literature, multiple methods such as matrix factorization and collaborative filtering exist and have been implemented for a long time, however recent studies show that some other approaches, especially using artificial neural networks, have promising improvements in this area of research. In this research, we propose a new hybrid recommender system that results in better performance. In the proposed system, the users are divided into two main categories, namely average users, and non-average users. Then, various machine learning and deep learning methods are applied within these categorie...
RT-PCR Accuracy Improvement for SARS-CoV-2 Detection Using Deep Neural Networks
SSRN Electronic Journal
Hibrit tavsiye sistemi
In the current era, the rapid pace of data volume is producing redundant information on the inter... more In the current era, the rapid pace of data volume is producing redundant information on the internet. Predicting the appropriate item for users has been a great challenge in information systems. As a result, recommender systems have emerged in this decade to resolve such problems. Many e-commerce platforms such as Amazon and Netflix are using some decent recommender systems to recommend their items to the users. Previously in the literature, multiple methods such as Matrix Factorization, Collaborative Filtering have been implemented for a long time, however in recent studies, neural networks have shown promising improvement in this area of research. In this research, motivated by the performance of hybrid systems, we propose a hybrid system for recommendation purposes. In the proposed system, the users are divided into two main categories: Average users and Non-average users. Both of these categories contain the users having similar behaviors towards the items. Various machine learn...
Formally Analyzing Continuous Aspects of Cyber-Physical Systems Modeled by Homogeneous Linear Differential Equations
Lecture Notes in Computer Science, 2015
Lecture Notes in Computer Science, 2013
The formal verification of cyber-physical systems is a challenging task mainly because of the inv... more The formal verification of cyber-physical systems is a challenging task mainly because of the involvement of various factors of continuous nature, such as the analog components or the surrounding environment. Traditional verification methods, such as model checking or automated theorem proving, usually deal with these continuous aspects by using abstracted discrete models. This fact makes cyber-physical system designs error prone, which may lead to disastrous consequences given the safety and financial critical nature of their applications. Leveraging upon the high expressiveness of higher-order logic, we propose to use higher-order-logic theorem proving to analyze continuous models of cyber-physical systems. To facilitate this process, this paper presents the formalization of the solutions of second-order homogeneous linear differential equations. To illustrate the usefulness of our foundational cyberphysical system analysis formalization, we present the formal analysis of a damped harmonic oscillator and a second-order op-amp circuit using the HOL4 theorem prover.
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Papers by Muhammad Sanwal