Oscar S. Siordia

• Computer Sicence PhD
• Rey Juan Carlos University

This study investigates the spatial and temporal dynamics of crime and social development in Mexico City between 2019 and 2023. By utilizing novel metrics—including crime rate (CR), crime harm per resident (CHIP), and crime harm per victim (CHIV)—alongside the Social Development Index (SDI), the study uncovers complex spatial relationships between...

Objectives The aim of this study is to evaluate the impact of the Pilares community program on crime rates and crime harm in Mexico City during the period from 2019 to 2023. Methods Employing a staggered difference-in-differences methodology, we examined the effects of the Pilares program on three crime metrics—Crime Rate (CR), Crime Harm per Resi...

Massive influxes of holopelagic Sargassum spp. (Sargassum natans and S. fluitans) have been causing major economic, environmental and ecological problems along the Caribbean coast of Mexico. Predicting the arrival of the sargassum as an aid to addressing these problems is a priority for the government, coastal communities and the society; both miti...

Mental health problems are one of the various ills that afflict the world’s population. Early diagnosis and medical care are public health problems addressed from various perspectives. Among the mental illnesses that most afflict the population is depression; its early diagnosis is vitally important, as it can trigger more severe illnesses, such as...

Natural Language Processing based technologies are transforming various sectors by facilitating new ways of providing services through Artificial Intelligence (AI). In this paper, we describe the methodology and present the challenges encountered during the creation of a Deep Learning-based model for classifying citizen service requests. Our system...

The pervasive adoption of GPS-enabled sensors has lead to an explosion on the amount of geolocated data that captures a wide range of social interactions. Part of this data can be conceptualized as event data, characterized by a single point signal at a given location and time. Event data has been used for several purposes such as anomaly detection...

This paper presents an ongoing research project that aims to propose a geopolitical analysis of anti-immigrant speech published on the Mexican twitosphere. Such speech has increasingly gained visibility and has been politically instrumentalized in the United States and some European countries. While Mexico has long defined itself as an emigration c...

The quarantine and stay-at-home measures implemented by most governments significantly impacted the volume and distribution of crime, and already, a body of literature exists that focuses on the effects of lockdown on crime. However, the effects of lockdown on firearm violence have yet to be studied. Within this context, this study analyzes reports...

Objectives To test the broken windows theory in the Mexican context. Methods Publicly available homicide counts and census data at the neighborhood level were used. Broken windows theory was operationalized through the use of social disorder and physical disorder measures. Measures were both calculated using PCA. For data analysis, we employed fou...

This volume contains the papers presented at the International Conference on Geospatial Information Sciences (iGISc 2019) held on October 23-25, 2019 in Mérida, Yucatán, Mexico. The iGISc 2019 aimed at serving as an articulating element of the research community around the issues addressed by Geospatial Information Sciences (GISc), including basic...

Abstract. In this paper we propose an aggregation strategy for geolocated Twitter posts based on a hierarchical definition of the regular activity patterns within a specific region. The aggregation yields a series of documents that are used to train a topic model. The resulting model is tested against the ones produced by two other aggregation stra...

This paper proposes a new technique for the extraction of regular activity patterns at different scales (resolution levels), mined from the microblogging platform Twitter. The approach is based on the recursive application of the DBSCAN clustering algorithm to the geolocated Twitter feed. The proposed technique includes a novel way to obtain 'avera...

Health services are on the top priorities for society, but up to now we have failed in make it universal all around the world. Nowadays information technologies, especially social networks have demonstrated its usefulness in different areas. This article describes the design and development of a social network platform focused on the physician-pati...

The objective of this text is to describe the three categories that the Drug Policy Program at the Center for Teaching and Research in Economics (CIDE-PPD) database comprises, their limitations, and their main features. Additionally, we explain what we believe to be the source of the database we originally received and analyze its accuracy by compa...

This paper proposes a new technique for the extraction of regular activity patterns at different scales (resolution levels), mined from the microblogging platform Twitter. The approach is based on the recursive application of the DBSCAN clustering algorithm to the geolocated Twitter feed. The proposed technique includes a novel way to obtain 'avera...

Hyperspectral imaging has been successfully utilized to locate clandestine graves. This study applied a Genetic Programming technique called Brain Programming (BP) for automating the design of Hyperspectral Visual Attention Models (H-VAM.), which is proposed as a new method for the detection of buried remains. Four graves were simulated and monitor...

The evaluation of subjective data is a very demanding task. The classification of the information gathered from human evaluators and the possible high noise levels introduced are ones of the most difficult issues to deal with. This situation leads to adopt individuals who can be considered as experts in the specific application domain. Thus, the de...

Sentiment analysis is a text mining task that determines the polarity of a given text, i.e., its positiveness or negativeness. Recently, it has received a lot of attention given the interest in opinion mining in micro-blogging platforms. These new forms of textual expressions present new challenges to analyze text because of the use of slang, ortho...

A topology synthesis method is introduced using genetic algorithms (GA) based on novelty search (NS). NS is an emerging meta-heuristic, that guides the search based on the novelty of each solution instead of the objective function. The synthesized topologies are current follower (CF) circuits; these topologies are new and designed using integrated...

Recently, sentiment analysis has received a lot of attention due to the interest in mining opinions of social media users. Sentiment analysis consists in determining the polarity of a given text, i.e., its degree of positiveness or negativeness. Traditionally, Sentiment Analysis algorithms have been tailored to a specific language given the complex...

Recently, sentiment analysis has received a lot of attention due to the interest in mining opinions of social media users. Sentiment analysis consists in determining the polarity of a given text, i.e., its degree of positiveness or negativeness. Traditionally, Sentiment Analysis algorithms have been tailored to a specific language given the complex...

Gender classification in social platforms and social media has become a relevant topic for the industry because of its impact in making decision process. Gender recognition in Twitter is a business intelligence tool focused on twitter data acquisition, analysis, and process, and it can be used in many ways to transform it into valuable business int...

Microblogging social networks are easily subverted by automated fake identities that amass disproportionately large influence. In this paper we present an effort to profile and screen such kind of accounts from existing and original ground truth obtained from the Twitter platform. Seventy-one explanatory properties solely extracted from profile and...

This paper proposes a new technique for the extraction of regular activity patterns at different scales, mined from the micro-blogging platform Twitter. The approach is based on the recursive application of the DBSCAN clustering algorithm to the geolocated Twitter feed. This technique includes a novel way to obtain averaged regular activity zones b...

Trends in geospatial technologies have led to the development of new powerful analysis and representation techniques that involve processing of massive datasets, some unstructured, some acquired from ubiquitous sources, and some others from remotely located sensors of different kinds, all of which complement the structured information produced on a...

This paper proposes a new technique for the extraction of regular activity patterns at different scales, mined from the micro-blogging platform Twitter. The approach is based on the recursive application of the DBSCAN clustering algorithm to the geolocated Twitter feed. This technique includes a novel way to obtain averaged regular activity zones b...

In this paper we present experiments for global polarity classification task of Spanish tweets for TASS 2015 challenge. In our methodology, tweets representation is focused on linguistic and polarity features such as lemmatized words, filter of content words, rules of negation, among others. In addition, different transformations are used (LDA, LSI...

Evaluating regional development implies the diagnosis of multiple dimensions. Many methodologies have been used to diagnose these dimensions of a particular region in order to conduct analysis and eventually to design or adjust public policies. All these analytical tools have focused on using multiple regional indicators for measuring some developm...

This paper presents a novelty system for the detection of driving-risk situations based on the knowledge acquired from traffic safety experts. A complete methodology to generate a driving-risk reference signal has been developed. A set of driving sessions was executed in a very realistic truck simulator, where several measures and visual informatio...

In this paper a novel methodology to measure driving risk based on hands activities and other driving variables is presented. The proposed methodology has been developed and tested in several driving sessions executed in two highly realistic simulators by several professional and non-professional drivers. The driver's hand positions are used to fee...

In this article, a novel accident analysis system is proposed to determine the main human factors involved in traffic accidents. Several tests of the system were carried out in a highly realistic truck simulator with a group of professional drivers. The data, collected with the system at the moments before traffic accidents, were used to generate a...

This paper presents a method for the selection of the optimal combination of experts' knowledge needed for the generation of a reliable driving risk ground truth. The driving risk of a controlled driving session, recorded in a highly realistic truck simulator, was evaluated by a large number of traffic safety experts. The risk evaluations were grou...

In this paper, a novel accident reproduction system for the identification of the main human factors involved on traffic accidents is presented. The system is based on a wireless in-vehicle Electronic Data Recorder that could be easily installed in any vehicle's cabin for the monitoring of the three basic elements of traffic safety: driver, road an...

The aim of this paper is to present a novelty methodology to develop similarity measures for classification of time series. First, a linear segmentation algorithm to obtain a section-wise representation of the series is presented. Then, two similarity measures are defined from the differences between the behavior of the series and the level of the...

In this paper a novelty method to combine knowledge of traffic safety experts, in order to detect driving risk situations, is presented. A set of driving sessions were executed in a very realistic truck simulator where several magnitudes and visual information from the vehicle, driver and road were collected. Two kind of experiments were designed:...

In this paper a novelty methodology to measure driving risk based on hands activity is presented. The proposed algorithm has been developed and tested on several driving sessions executed on a highly realistic truck simulator. The hands positions are used to feed a risk buffer that is in charge of penalizing wrong hands activities and praising good...

In this paper, a novelty methodology for the representation and similarity measurement of sequential data is presented. First, a linear segmentation algorithm based on feature points is proposed. Then, two similarity measures are defined from the differences between the behavior and the mean level of the sequential data. These similarities are calc...

In this paper, a methodology to recognize driving risk situations as the solution of a combination of information problem is presented. A collection of simulated sessions in a highly realistic truck simulator were designed and executed. Several internal truck magnitudes and visual information from the driver and the road were collected in each sess...

In this paper, an in-vehicle complaint recording device is presented. The device is divided in independent systems for image and audio data acquisition and storage. The systems, designed to work under in-vehicle complaint devices, use existent in-vehicle wireless architectures for its communication. Several tests of the recording device in a highly...

A novel multidisciplinary system for the automatic driving risk level classification is presented. The data considered involves the three basic traffic safety elements (driver, road, and vehicle), as well as knowledge from traffic experts. The driving experiments were conducted in a truck cabin simulator handled by a professional driver, considerin...

This document describes a method for classifying images of blood cells. Three different classes of cells are used: Band Neutrophils, Eosinophils and Lymphocytes. The image pattern is projected down to a lower dimensional sub space using PCA; the probability density function for each class is modeled with a Gaussian mixture using the EM-Algorithm. A...

This work describes the design of software that allows the programming of autonomous, omnidirectional mobile robots controlled by FPGA 's and embedded microprocessors, in a very intuitive visual environment. The software and robots described in this work were designed to be used in the teaching of different areas of engineering. With the use of win...