output
20132026
most citedCrime Prediction Using Machine Learning and Deep Learning: A Systematic Review and Future Directions

184 citations

14 papers

q-bio.GN2026

Detecting and Correcting Sample-by-Sample Scale Distortion in RNA Sequencing Data

Christopher Thron, Farhad Jafari

RNA sequencing (RNA-seq) is the conventional genome-scale approach used to capture the expression levels of all detectable genes in a biological sample. This is now regularly used…

cs.DC2025★ 1 cited

LLM-HPC++: Evaluating LLM-Generated Modern C++ and MPI+OpenMP Codes for Scalable Mandelbrot Set Computation

Patrick Diehl, Noujoud Nader, Deepti Gupta

Parallel programming remains one of the most challenging aspects of High-Performance Computing (HPC), requiring deep knowledge of synchronization, communication, and memory models.…

cs.SE2025

Can LLMs Find Bugs in Code? An Evaluation from Beginner Errors to Security Vulnerabilities in Python and C++

Akshay Mhatre, Noujoud Nader, Patrick Diehl +1

Large Language Models (LLMs) such as ChatGPT-4, Claude 3, and LLaMA 4 are increasingly embedded in software/application development, supporting tasks from code generation to debugg…

cs.CR2023★ 19 cited

Privacy-Preserving Data Sharing in Agriculture: Enforcing Policy Rules for Secure and Confidential Data Synthesis

Anantaa Kotal, Lavanya Elluri, Deepti Gupta +2

Big Data empowers the farming community with the information needed to optimize resource usage, increase productivity, and enhance the sustainability of agricultural practices. The…

cs.LG2023★ 21 cited

Recent Advancements in Machine Learning For Cybercrime Prediction

Lavanya Elluri, Varun Mandalapu, Piyush Vyas +1

Cybercrime is a growing threat to organizations and individuals worldwide, with criminals using sophisticated techniques to breach security systems and steal sensitive data. This p…

cs.LG2023★ 184 cited

Crime Prediction Using Machine Learning and Deep Learning: A Systematic Review and Future Directions

Varun Mandalapu, Lavanya Elluri, Piyush Vyas +1

Predicting crime using machine learning and deep learning techniques has gained considerable attention from researchers in recent years, focusing on identifying patterns and trends…

physics.gen-ph2021★ 1 cited

Sliced, not Splitted: a Better Alternative to Many-Worlds?

Christopher Thron, Braeden Welsch

The many-worlds interpretation (MWI) of quantum mechanics is currently experiencing a popular resurgence, propelled by such prominent and articulate physicists as Sean Carroll, Dav…

math.GM2021

Math That Matters: Enhancing Academic Mathematics' Impact on Society

Christopher Thron, Monira Taj Elsir Hamid Ali

Most if not all of today's revolutionary technologies have a common foundation, namely the intelligent use of information. It is clear that computers play a central role: but the c…

eess.SY2020

High Performance Low Complexity Multitarget Tracking Filter for a Array of Non-directional Sensors

Christopher Thron, Khoi Tran, Joseph Raquepas

This paper develops an accurate, efficient filter (called the `TT filter') for tracking multiple targets using a spatially-distributed network of amplitude sensors that estimate di…

physics.gen-ph2015★ 2 cited

An Accumulative Model for Quantum Theories

Christopher Thron

For a general quantum theory that is describable by a path integral formalism, we construct a mathematical model of the universe as a sample point of an accumulative stochastic pro…

cs.NI2015★ 8 cited

A Metropolis Approach for Mesh Router Nodes placement in Rural Wireless Mesh Networks

Jean Louis Ebongue Kedieng Fendji, Christopher Thron, Jean Michel Nlong

Wireless mesh networks appear as an appealing solution to reduce the digital divide between rural and urban regions. However the placement of router nodes is still a critical issue…

math.OC2014★ 1 cited

Very Low-Complexity Algorithms for Beamforming in Two-Way Relay Systems

Chris Thron, Ahsan Aziz

In this paper, we present a novel solution for optimal beamforming in a two-way relay (TWR) systems with perfect channel state information. The solution makes use of properties of…

math.OC2014★ 8 cited

Optimal control of anthracnose using mixed strategies

David Jaurès Fotsa Mbogne, Christopher Thron

In this paper we propose and study a spatial diffusion model for the control of anthracnose disease in a bounded domain. The model is a generalization of the one previously develop…

math.OC2013★ 8 cited

Mathematical modelling and optimal control of anthracnose

David Fotsa, Elvis Houpa, David Békollé +2

In this paper we propose two nonlinear models for the control of anthracnose disease. The first is an ordinary differential equation (ODE) model which represents the within-host ev…