Tootfinder

Generating Java Methods: An Empirical Assessment of Four AI-Based Code Assistants
Vincenzo Corso, Leonardo Mariani, Daniela Micucci, Oliviero Riganelli
https://arxiv.org/abs/2402.08431

Generating Java Methods: An Empirical Assessment of Four AI-Based Code Assistants
AI-based code assistants are promising tools that can facilitate and speed up code development. They exploit machine learning algorithms and natural language processing to interact with developers, suggesting code snippets (e.g., method implementations) that can be incorporated into projects. Recent studies empirically investigated the effectiveness of code assistants using simple exemplary problems (e.g., the re-implementation of well-known algorithms), which fail to capture the spectrum and n…

A Model for Assessing Network Asset Vulnerability Using QPSO-LightGBM
Xinyu Li, Yu Gu, Chenwei Wang, Peng Zhao
https://arxiv.org/abs/2403.07029 https://

A Model for Assessing Network Asset Vulnerability Using QPSO-LightGBM
With the continuous development of computer technology and network technology, the scale of the network continues to expand, the network space tends to be complex, and the application of computers and networks has been deeply into politics, the military, finance, electricity, and other important fields. When security events do not occur, the vulnerability assessment of these high-risk network assets can be actively carried out to prepare for rainy days, to effectively reduce the loss caused by …

This https://arxiv.org/abs/2403.05692 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Privacy-Preserving Sharing of Data Analytics Runtime Metrics for Performance Modeling
Performance modeling for large-scale data analytics workloads can improve the efficiency of cluster resource allocations and job scheduling. However, the performance of these workloads is influenced by numerous factors, such as job inputs and the assigned cluster resources. As a result, performance models require significant amounts of training data. This data can be obtained by exchanging runtime metrics between collaborating organizations. Yet, not all organizations may be inclined to publicl…

RobotCycle: Assessing Cycling Safety in Urban Environments
Efimia Panagiotaki, Tyler Reinmund, Brian Liu, Stephan Mouton, Luke Pitt, Arundathi Shaji Shanthini, Matthew Towlson, Wayne Tubby, Chris Prahacs, Daniele De Martini, Lars Kunze
https://arxiv.org/abs/2403.07789

RobotCycle: Assessing Cycling Safety in Urban Environments
This paper introduces RobotCycle, a novel ongoing project that leverages Autonomous Vehicle (AV) research to investigate how cycling infrastructure influences cyclist behaviour and safety during real-world journeys. The project's requirements were defined in collaboration with key stakeholders (i.e. city planners, cyclists, and policymakers), informing the design of risk and safety metrics and the data collection criteria. We propose a data-driven approach relying on a novel, rich dataset of di…

Physics-Guided Inverse Regression for Crop Quality Assessment
David Shulman, Assaf Israeli, Yael Botnaro, Ori Margalit, Oved Tamir, Shaul Naschitz, Dan Gamrasni, Ofer M. Shir, Itai Dattner
https://arxiv.org/abs/2403.08653

Physics-Guided Inverse Regression for Crop Quality Assessment
We present an innovative approach leveraging Physics-Guided Neural Networks (PGNNs) for enhancing agricultural quality assessments. Central to our methodology is the application of physics-guided inverse regression, a technique that significantly improves the model's ability to precisely predict quality metrics of crops. This approach directly addresses the challenges of scalability, speed, and practicality that traditional assessment methods face. By integrating physical principles, notably Fi…

Assessing the Privacy Risk of Cross-Platform Identity Linkage using Eye Movement Biometrics
Samantha Aziz, Oleg Komogortsev
https://arxiv.org/abs/2402.08655

Assessing the Privacy Risk of Cross-Platform Identity Linkage using Eye Movement Biometrics
The recent emergence of ubiquitous, multi-platform eye tracking has raised user privacy concerns over re-identification across platforms, where a person is re-identified across multiple eye tracking-enabled platforms using personally identifying information that is implicitly expressed through their eye movement. We present an empirical investigation quantifying a modern eye movement biometric model's ability to link subject identities across three different eye tracking devices using eye movem…

Convex cones, assessment functions, balanced attributes
Ignacy Kaliszewski
https://arxiv.org/abs/2403.07829 https://arxiv.org/pdf/240…

Convex cones, assessment functions, balanced attributes
We investigate a class of polyhedral convex cones, with $R^k_+$ (the nonegative orthant in $\mathbb{R}^k$) as a special case. We start with the observation that for convex cones contained in $\mathbb{R}^k$, the respective cone efficiency is inconsistent with the Pareto efficiency, the latter being deeply rooted in economics, the decision theory, and the multiobjective optimization theory. Despite that, we argue that convex cones contained in $\mathbb{R}^k$ and the respective cone efficiency are…

Multi-Apartment Rent Division
Ariel D. Procaccia, Benjamin Schiffer, Shirley Zhang
https://arxiv.org/abs/2403.08051 https://arxiv.org…

Multi-Apartment Rent Division
Rent division is the well-studied problem of fairly assigning rooms and dividing rent among a set of roommates within a single apartment. A shortcoming of existing solutions is that renters are assumed to be considering apartments in isolation, whereas in reality, renters can choose among multiple apartments. In this paper, we generalize the rent division problem to the multi-apartment setting, where the goal is to both fairly choose an apartment among a set of alternatives and fairly assign ro…

Convex cones, assessment functions, balanced attributes
Ignacy Kaliszewski
https://arxiv.org/abs/2403.07829 https://arxiv.org/pdf/240…

Convex cones, assessment functions, balanced attributes
We investigate a class of polyhedral convex cones, with $R^k_+$ (the nonegative orthant in $\mathbb{R}^k$) as a special case. We start with the observation that for convex cones contained in $\mathbb{R}^k$, the respective cone efficiency is inconsistent with the Pareto efficiency, the latter being deeply rooted in economics, the decision theory, and the multiobjective optimization theory. Despite that, we argue that convex cones contained in $\mathbb{R}^k$ and the respective cone efficiency are…

Multi-Apartment Rent Division
Ariel D. Procaccia, Benjamin Schiffer, Shirley Zhang
https://arxiv.org/abs/2403.08051 https://arxiv.org…

Multi-Apartment Rent Division
Rent division is the well-studied problem of fairly assigning rooms and dividing rent among a set of roommates within a single apartment. A shortcoming of existing solutions is that renters are assumed to be considering apartments in isolation, whereas in reality, renters can choose among multiple apartments. In this paper, we generalize the rent division problem to the multi-apartment setting, where the goal is to both fairly choose an apartment among a set of alternatives and fairly assign ro…