Luis Carlos Gonzalez Gurrola

• PhD in Information Technology
• Professor at Autonomous University of Chihuahua

Social networks have become one of the most popular ways for people to communicate with others and get informed. For this reason, these platforms are being widely used to spread propaganda and thereby influence the beliefs, opinions and actions of their users. Despite its relevance, current computational approaches to detect propaganda are mainly f...

Being able to predict when an invoice will be paid becomes a critical point for companies dedicated to factoring. This business model is based on purchasing outstanding invoices from businesses that have slow paying customers and are looking to boost cash flow. However, due to the complexity of data related to invoices and the fact that the decisio...

Social media is frequently plagued with undesirable phenomena such as cyberbullying and abusive content in the form of hateful and racist posts. Therefore, it is crucial to study and propose better mechanisms to automatically identify communication that promote hate speech, hostility, and aggressiveness. Traditional approaches have only focused on...

Speaker identification is the process through which a person can be identified by using the physical characteristics of his voice. In recent years, this identification is done by using artificial intelligence algorithms along to feature extract methods from the speech signal such as the MFCCs (Mel Frequency Cepstral Coefficients). Text-independent...

Author profiling (AP) is a highly relevant natural language processing (NLP) problem; it deals with predicting features of authors such as gender, age and personality traits. It is done by analyzing texts written by the authors themselves; take for instance documents such as books, articles, and more recently posts in social media platforms. In the...

As a first step towards decreasing greenhouse gas emissions originating from transportation, it is critical that we create efficient systems for monitoring individual travel patterns and the associated carbon footprints. To this end, this paper presents a CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xli...

Insurance Telematics is a recent service that is offered to drivers where a sensing platform measures vehicle’s dynamics with the ultimate goal of inferring the level of risk that the driver experiences on the road. For this to happen, a robust set of sensors must be deployed within the vehicle and effective algorithms to process and classify drivi...

Currently, self-harm is considered one of the leading causes of death by suicide in young people. Timely detection of self-inflicted injury is important to help people before the illness gets worse, minimizing disabilities and returning them to their normal life. A popular way for people to share information is using social media platforms, where t...

Over the last few years, studies related to the detection of mental disorders in social media have been increasing. The latter because the awareness created by health campaigns that emphasizes the commonness of these disorders among all of us has motivated the creation of new datasets, many of them extracted from social media platforms. In this stu...

Every year, new Convolutional Neural Network (CNN) architectures appear to deal with different problems in the activity of image and video recognition. These architectures usually work along the ImageNet dataset for looking for the best performance of the CNNs without taking into account the video task where they are used. This can represent a prob...

Hypervolume (HV) has become one of the most popular indicators to assess the quality of Pareto front approximations. However, the best algorithm for computing these values has a computational complexity of O(Nk/3polylog(N)) for N candidate solutions and k objectives. In this study, we propose a regression-based approach to learn new mathematical ex...

Public health surveillance via social media can be a useful tool to identify and track potential cases of a disease. The aim of this research was to design a method for identifying tweets describing potential Covid-19 cases. The proposed method uses a Wide & Deep (W&D) architecture, which combines two learning branches fed from different features t...

Social networks have become the main means of communication and interaction between people. In them, users share information and opinions, but also their experiences, worries, and personal concerns. Because of this, there is a growing interest in analyzing this kind of content to identify people who commit self-harm, which is often one of the first...

Millions of people around the world are affected by one or more mental disorders that interfere in their thinking and behavior. A timely detection of these issues is challenging but crucial, since it could open the possibility to offer help to people before the illness gets worse. One alternative to accomplish this is to monitor how people express...

A positive consequence of the existence of a more inclusive society is the appearance of protocols to help identify those in need. One of these protocols is the application of tests with the aim to detect learning disabilities in children so that opportune intervention could be made. These advances, though, also pose challenges to the responsible t...

Different mental disorders affect millions of people around the world, causing significant distress and interference to their daily life. Currently, the increased usage of social media platforms, where people share personal information about their day and problems, opens up new opportunities to actively detect these problems. We present a new appro...

In this study we introduce the k-Strongest Strengths (kSS) Classification Algorithm, a novel approach for classification problems based on the well-known k-Nearest Neighbor (kNN) classifier. The proposed kSS method is motivated by an analogy to the Law of Universal Gravitation. The novelty of kSS resides in that instead of only using the neighbors’...

In this study we propose a novel method to generate Document Embeddings (DEs) by means of evolving mathematical equations that integrate classical term frequency statistics. To accomplish this, we employed a Genetic Programming (GP) strategy to build competitive formulae to weight custom Word Embeddings (WEs), produced by cutting edge feature extra...

Much has been said regarding the automatic quality assessment of roadways by analyzing data from inertial sensors either fixed to the vehicle or embedded into the drivers' smartphones. Literature is vast in models to, given a record of sensor readings, determine if the sample corresponds to a pothole or speed bump. Acknowledging this advance this s...

In this paper we describe our participation for the Aggressiveness Detection Track in the second edition of MEX-A3T. We evaluate different strategies for text classification, including classifiers such as Support Vector Machines and a Multilayer Perceptron trained on n-grams (words and characters) and word embeddings. We also study the inclusion of...

Road transportation is of critical importance for a nation, having profound effects in the economy, the health and life style of its people. With the growth of cities and populations come bigger demands for mobility and safety, creating new problems and magnifying those of the past. New tools are needed to face the challenge, to keep roads in good...

Aggressive driving behavior is one of the leading causes of road accidents worldwide. One way to ameliorate this situation is to collect and analyze driving patterns with the intention of promoting driving awareness, a task that has been called driving analytics (DA). DA employing the driver's smartphone has attracted attention from the community g...

Dependence on personal computers has required the development of security mechanisms to protect the information stored in these devices. There have been different approaches to profile user behavior to protect information from a masquerade attack; one such recent approach is based on user file-access patterns. In this paper, we propose a novel clas...

Nowadays social media platforms are the most popular way for people to share information, from work issues to personal matters. For example , people with health disorders tend to share their concerns for advice, support or simply to relieve suffering. This provides a great opportunity to proactively detect these users and refer them as soon as poss...

In this study, an optimization with genetic algorithm and multi-objective genetic algorithm for vehicle transportation route is performed. The objective function used in the genetic algorithm is calculated using an equation with the sum of the values of the total distance and the number of active vehicles. For the multi-objective genetic algorithm...

The kNN algorithm has three main advantages that make it appealing to the community: it is easy to understand, it regularly offers competitive performance and its structure can be easily tuning to adapting to the needs of researchers to achieve better results. One of the variations is weighting the instances based on their distance. In this paper w...

The kNN algorithm has three main advantages that make it appealing to the community: it is easy to understand, it regularly offers competitive performance and its structure can be easily tuning to adapting to the needs of researchers to achieve better results. One of the variations is weighting the instances based on their distance. In this paper w...

The kNN algorithm has three main advantages that make it appealing to the community: it is easy to understand, it regularly offers competitive performance and its structure can be easily tuning to adapting to the needs of researchers to achieve better results. One of the variations is weighting the instances based on their distance. In this paper w...

La detección de anomalías es una tarea de interés en muchas aplicaciones del mundo real cuyo objetivo es identificar el comportamiento irregular de un proceso basado en el aprendizaje de cómo éste se comporta normalmente. En este trabajo, presentamos una versión MapReduce de una estrategia que ha demostrado ser exitosa para encontrar valores atípic...

According to the World Health Organization, recent years have seen a dramatic increase in the number of car accidents worldwide. In an attempt to ameliorate this situation, the automotive and telematics industry has tried to develop technology that can help drivers make better and safer decisions. One approach is to develop systems that give feedba...

Road traffic injuries are a serious concern in emerging economies. Their death toll and economic impact are shocking, with 9 out of 10 deaths occurring in low or middle-income countries; and road traffic crashes representing 3% of their gross domestic product. One way to mitigate these issues is to develop technology to effectively assist the drive...

A wide range of new possibilities in the area of intelligent transportation systems (ITS) emerged when sensors, such as accelerometers, were introduced in practically every smartphone. A clear example is using a driver's smartphone to detect the vertical movement experienced by the vehicle when passing over a pothole or bump; in other words, sensin...

Given that thousands of applications are already available for smartphones, we may be inclined to believe that ubiquitous computing is just around the corner, with online processing in these mobile devices. But, how well prepared is current smartphone technology to support the execution of demanding algorithms? Surprisingly, few researchers have ad...

Accurately classifying roadway surface disruptions (RSDs) plays a crucial role to enhance quality transportation and road safety. To this end, smartphones are becoming an ad hoc tool to collect road data, while the user is at the steering wheel. In this paper, for the first time, sensed data are represented with a novel technique inspired in the ba...

The Vehicle Routing Problem with Route Balancing (VRPRB) is a biobjective version of the original Vehicle Routing Problem (VRP) in which, besides minimizing the total distance traveled by the vehicles involved, the balance among route loads is also pursued. Different objective functions (OFs) to achieve balanced route configurations have been propo...

In 2011 it was presented one of the most devastating droughts in northern Mexico that seriously affected the activities of the productive sector. The aim of this study was to predict the next event of drought in the northwest region of the state of Chihuahua, Mexico. Information of 40 years was used in four weather stations. The ARIMA models with n...

Given their ubiquity and sensing capabilities, current smartphones have been used to explore different real-life tracking and monitoring scenarios. Particularly, in the domain of Intelligent Transportation Systems (ITS), the exact orientation of the smartphone must be known to gain full advantage of the data provided by its internal accelerometers....

Given their ubiquity and sensing capabilities, current smart-phones have been used to explore different real-life tracking and monitoring scenarios. Particularly, in the domain of Intelligent Transportation Systems (ITS), the exact orientation of the smartphone must be known to gain full advantage of the data provided by its internal accelerometers...

Smartphone-based applications for Intelligent Transportation Systems (ITS) have become a real possibility because of the sensing and computing capabilities of these devices. In this work we employ smartphones' accelerometers to sense the quality of roads, detecting the perturbations encountered by the vehicle. The ultimate goal of this line of work...

Location-based services require to process and infer knowledge based on the understanding of people daily activities. This information acquires relevance in cases when elder people live alone since it could be used to infer facts about his/her health. In this paper a platform for getting location and activity data for indoors is presented. Gathered...

The body-bar Pebble Game (PG) algorithm is commonly used to calculate network rigidity properties in proteins and polymeric materials. To account for fluctuating interactions such as hydrogen bonds, an ensemble of constraint topologies are sampled, and average network properties are obtained by averaging PG characterizations. At a simpler level of...

commitment of time and effort that is necessary to the management of the household can be very significant, especially when nurturing activity has to be interwoven with other activities. It is necessary to understand the management of activities and spaces when a parent has to take care of a child while performing chores simultaneously. In this wor...

In developed countries large-scale technology is used for the monitoring and management of road infrastructure. Sensor networks together with surveillance cameras help identify elements disturbing cars mobility. On the contrary, in developing countries, the lack of this level of infrastructure makes the task of roads maintenance and traffic control...

Previous works have demonstrated that protein rigidity is related to thermodynamic stability, especially under conditions that favor formation of native structure. Mechanical network rigidity properties of a single conformation are efficiently calculated using the integer body-bar Pebble Game (PG) algorithm. However, thermodynamic properties requir...

The Pebble Game (PG) algorithm is an efficient method to characterize protein flexibility. The PG calculates several mechanical graph rigidity quantities based on a network of chemical interactions. Because noncovalent chemical interactions continually break and reform, a distinct PG calculation is necessary for each network topology. As such, equi...

We report the results of pyrosequencing of DNA collected from the activated sludge basin of a wastewater treatment plant in Charlotte, NC. Using the 454-FLX technology, we generated 378,601 sequences with an average read length of 250.4 bp. Running the 454 assembly algorithm over our sequences yielded very poor assembly, with only 0.3% of our seque...

Abstract This paper presents a genetic algorithm for an important computational biology problem. The problem appears in the computational part of a new proposal for DNA sequencing denominated sequencing by hybridization. The general usage of this method for real sequencing purposes depends mainly on the development of good algorithmic procedures so...

This paper presents a genetic algorithm for the shortest common superstring problem. The problem appears in the computational part of a deoxyribonucleic acid (DNA) sequencing procedure as well as in data compression. The proposed genetic algorithm is based on a recently proposed algorithm for the sequencing by hybridization (SBH) problem. The algo...

Many real world problems can be modeled as the shortest common superstring problem. This problem has several important applications in areas such as DNA sequencing and data compression.

This paper presents a genetic algorithm for a computational biology problem. The problem appears in the computational part of a new deoxyribonucleic acid (DNA) sequencing procedure denominated sequencing by hybridization (SBH). The proposed genetic algorithm is an improvement over a recently proposed algorithm in the literature. The improvement is...