This research paper presents an analytical approach to earthquake time-series forecasting using the Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) models. The objective of this study is to investigate the ...

Cyber attacks are a major and routine threat to the modern society. This highlights the importance of forecasting (i.e., predicting) cyber attacks, just like weather forecasting in the real world. In this paper, we present a study on ...

The coronavirus disease 2019 (COVID-19) was a cause of concern in the healthcare system and increased the need for disease severity indicators. However, they still vary in use to evaluate in-hospital outcomes and ...

Smart nonintrusive load monitoring (NILM) represents a cost‐efficient technology for observing power usage in buildings. It tackles several challenges in transitioning into a more effective, sustainable, and digital energy efficiency environment. ...

Large-scale services depend on Continuous Integration/Continuous Deployment (CI/CD) processes to maintain their agility and code-quality. Change-based testing plays an important role in finding bugs, but testing after every change is prohibitively ...

Social debt has been defined as the presence in a project of costly sub-optimal organizational conditions, e.g., non-cohesive development communities whose members have communication or coordination issues. Community smells are indicators of such sub-...

In this document, we present the replication package of the paper "Understanding Community Smells Variability: A Statistical Approach" accepted at the 43rd International Conference on Software Engineering - Software Engineering in Society Track (ICSE '...

Forecasting, especially high‐dimensional forecasting, is becoming more and more sought after, particularly as computing resources increase in both size and speed. Flow field forecasting is a general purpose regression‐based forecasting method that ...

Forecasting, especially high‐dimensional forecasting, is becoming more and more sought after, particularly as computing resources increase in both size and speed. Flow field forecasting is a general purpose regression‐based forecasting method that has ...

The BIRDS workshop aimed to foster the cross-fertilization of Information Science (IS), Information Retrieval (IR) and Data Science (DS). Recognising the commonalities and differences between these communities, the proposed full-day workshop brought ...

In this paper, I present applying statistical language models to improve code completion in Pharo. In particular, the goal is to use n-gram models for sorting the completion candidates and, in such a way, increase the relevancy of the suggested ...

This study studies the influence of country attributes on the number of secure shell attacks originating from it detected by the author's honeynet. Four statistical models are described, based on three sources of data from various countries. The studied ...

This is a survey of the main achievements in the methodology and theory of stochastic global optimization. It comprises two complimentary directions: global random search and the methodology based on the use of stochastic models about the objective ...

This paper reviews the interplay between global optimization and probability models, concentrating on a class of deterministic optimization algorithms that are motivated by probability models for the objective function. Some complexity results are ...

In this paper, we propose a hybrid method for the spoken Tunisian dialect understanding within a limited task. This method couples a discriminative statistical method with a domain ontology. The statistical method is based on conditional random field (...

We address the problem of image retrieval using textual queries. In particular, we focus on descriptive queries that can be either in the form of simple captions (e.g., ``a brown cat sleeping on a sofa''), or even long descriptions with multiple ...

This paper investigates the statistical properties of human motion-based harvested power, and provides models for the distribution, auto-correlation and cross-correlation of harvested power at different body locations, namely left wrist, right wrist, left ...

The problem of multi-objective optimisation with ‘expensive’ ‘black-box’ objective functions is considered. An algorithm is proposed that generalises the single objective P-algorithm constructed using the statistical model of multimodal functions and ...

When high-dimensional data is visualized in a 2D plane by using parametric projection algorithms, users may wish to manipulate the layout of the data points to better reflect their domain knowledge or to explore alternative structures. However, few ...

Statistical models of source code can be used to improve code completion systems, assistive interfaces, and code compression engines. We are developing a statistical model where programs are represented as syntax trees, rather than simply a stream of ...