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2019 | Book

Solving the Multi-Period Water Distribution Network Design Problem with a Hybrid Simulated Anealling Read chapter Read first chapter

Computer Science – CACIC 2018

24th Argentine Congress, Tandil, Argentina, October 8–12, 2018, Revised Selected Papers

Editors: Patricia Pesado, Claudio Aciti

Publisher: Springer International Publishing

Book Series : Communications in Computer and Information Science

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

This book constitutes revised selected papers from the 24th Argentine Congress on Computer Science, CACIC 2018, held in Tandil, Argentina, in October 2018.

The 26 papers presented in this volume were carefully reviewed and selected from a total of 155 submissions. They were organized in topical sections named: Agents and Systems; Distributed and Parallel Processing; Technology Applied to Education; Graphic Computation, Images and Visualization; Software Engineering; Databases and Data Mining; Hardware Architectures, Networks, and Operating Systems; Innovation in Software Systems; Signal Processing and Real-Time Systems; Computer Security; Innovation in Computer Science Education; and Digital Governance and Smart Cities.

Table of Contents

Frontmatter

Agents and Systems

Frontmatter
Solving the Multi-Period Water Distribution Network Design Problem with a Hybrid Simulated Anealling
Abstract
This work presents an optimization technique based on Simulated Annealing (SA) to solve the Water Distribution Network Design problem, considering multi-period restrictions with time varying demand patterns. The design optimization of this kind of networks is an important issue in modern cities, since a safe, adequate, and accessible supply of potable water is one of the basic necessities of any human being. Given the complexity of this problem, the SA is improved with a local search procedure, yielding a hybrid SA, in order to obtain good quality networks designs. Additionally, four variants of this algorithm based on different cooling schemes are introduced and analyzed. A broad experimentation using different benchmark networks is carried out to test our proposals. Moreover, a comparison with an approach from the literature reveals the goodness to solve this network design problem.
Carlos Bermudez, Carolina Salto, Gabriela Minetti

Distributed and Parallel Processing

Frontmatter
Checkpoint and Restart: An Energy Consumption Characterization in Clusters
Abstract
The fault tolerance method currently used in High Performance Computing (HPC) is the rollback-recovery method by using checkpoints. This, like any other fault tolerance method, adds an additional energy consumption to that of the execution of the application. The objective of this work is to determine the factors that affect the energy consumption of the computing nodes on homogeneous cluster, when performing checkpoint and restart operations, on SPMD (Single Program Multiple Data) applications. We have focused on the energetic study of compute nodes, contemplating different configurations of hardware and software parameters. We studied the effect of performance states (states P) and power states (states C) of processors, application problem size, checkpoint software (DMTCP) and distributed file system (NFS) configuration. The results analysis allowed to identify opportunities to reduce the energy consumption of checkpoint and restart operations.
Marina Morán, Javier Balladini, Dolores Rexachs, Emilio Luque
Energy Consumption Analysis and Time Estimation Model in GPU Cluster and MultiGPU in a High Computational Demand Problem
Abstract
In this article, the energy used in two GPU clusters and MultiGPU to solve the n-body problem is analyzed. A time estimation model is developed and validated. Solutions are described and results shown, together with a performance and energy consumption analysis for the case study.
Erica Montes de Oca, Laura De Giusti, Armando De Giusti, Marcelo Naiouf

Technology Applied to Education

Frontmatter
Advances in Test Personalization and Adaptation in a Virtual Learning Environment
Abstract
This paper states the analysis of an experience of personalization and adaptation for the learning of university students. The experience presents tests of formative evaluation, personalized and adapted in a Virtual Learning Environment, as a complement on site teaching. The objective of this communication is exposing, as a contribution, our adaptive methods for the learning experience. The personalization of the tests was based on the identification of the learning styles and the levels of previous knowledge of the students. The experience started in the year 2014 and still continues. The results of the analysis show that our techniques of personalization and adaptation, which have been refined as time went by, improve the students’ learning and guide the professors in the decision-making that have an impact in the optimization of the pedagogical proposal.
Marcela Gonzalez, Delia Esther Benchoff, Constanza Huapaya, Cristian Remon, Guillermo Lazzurri, Leonel Guccione, Franscisco Lizarralde
Learning Objects. Case Studies
Abstract
In this article, we present a review on the topic of Learning Objects (LOs) based on case studies presented in the bibliography. We start by considering the origins of the term, various conceptualizations, and then focus on LO reutilization. The case studies selected are used to analyze aspects pertaining to LO creation and use in specific educational contexts. The results obtained can be used to consider issues such as reasons why educators choose to work with LOs, LO design methodologies (technological, pedagogical, hybrid), types of design scenarios (audiovisual, interactive, mixed), development tools (for assembling LO, generating contents, generating activities/self-evaluations, loading metadata), publication environments (LO repositories and Virtual Teaching and Learning Environments), and assessment processes (tests with students and educators). This review reveals a positive, progressing outlook as regards LO creation and their incorporation/use in educational contexts. There are also some aspects that would have to be considered in more detail in relation to LO reutilization that are good for analysis and coming up with new lines of action.
María Lucía Violini, Cecilia Verónica Sanz
A Nomadic Testbed for Teaching Computer Architecture
Abstract
A nomadic laboratory or testbed, based on Raspberry Pi 3 computers and Arduino microcontrollers, has been developed in order to teach subjects related to computer architecture. The testbed can be transported to the classroom. Students can access it through the available network, which can be a wireless LAN, wired LAN o a custom network. Students can access without constraints to the platforms, therefore there are a wide range of possible experiments. This laboratory was used during 2017 for practical works in the course Introduction to Technology, and during 2018 in two courses of Computers Architecture at Universidad Nacional of Cuyo and in a course of Wireless Networks at Universidad de Mendoza. Some of the experiments that are been carried out by students are: to explore and analyse the architecture of computers through Linux commands, write and run programs on different programing languages, input and output operations through memory mapped addressing and isolated addressing, write interrupt service routines in order to service interrupts, multithreading programing, explore memory maps, CPU features, etc. This paper describes the testbed architecture, experiments performed by students in the mentioned subjects, present the students feedback, and describes the possible methods in order to integrate it to a remote laboratory.
Pablo D. Godoy, Carlos G. García Garino, Ricardo L. Cayssials

Graphic Computation, Images and Visualization

Frontmatter
Evaluating an End-to-End Process for Herpetological Heritage Digital Preservation
Abstract
Documentation of institutional biological collections are essential for scientific studies and conservation of the biodiversity of a region. In particular, preserved specimens require the development of a short- and long-term plan to prevent damage.
In this context, the 3D digitisation of this type of documentation provides innovative mechanisms to safeguard the valuable information provided by the collections and at the same time prevent any possible loss of information. At the moment, the potential of laser scanning in model reconstruction is well-known, but developed works using this method for 3D construction reveal a lack of reliable, precise and flexible solutions. Furthermore, visualisation of results is often very useless and does not go beyond web-based applications.
This work presents an analysis of 3D modelling using two digitisation techniques: laser scanning and photogrammetry; combined with real time VR and AR visualizations and 3D printing. Subsequently, in accordance with the processes carried out, qualitative and quantitative evaluations of the results obtained are accomplished.
Nicolás Jofré, Graciela Rodríguez, Yoselie Alvarado, Jacqueline Fernandez, Roberto Guerrero
Color Image Enhancement Using a Multiscale Morphological Approach
Abstract
Color image enhancement has been widely applied in a variety of applications from different scientific areas. On the other hand, mathematical morphology is a theory that deals with describing shapes using sets and, therefore, it provides a number of useful tools for image enhancement. Despite its utility, one of the challenges of this theory, when applied to color images, is to determine an order between the components of the image. Color images are represented by multidimensional data structures, which implies that there is no natural order between their components. In this work we propose an image enhancement method for color images that uses the extension of the multiscale mathematical morphology with different color spaces and ordering methods. The experiments carried out show that the proposed method generates competitive results using different ordering methods in terms of both local and global contrast, as well as the color quality of the image.
Raul Mendez, Rodolfo Cardozo, José Luis Vázquez Noguera, Horacio Legal-Ayala, Julio César Mello Román, Sebastian Grillo, Miguel García-Torres
An Approach to Automated Recognition of Pavement Deterioration Through Machine Learning
Abstract
Roads are composed of various sorts of materials and with the constant use they expose different kinds of cracks or potholes. The aim of the current research is to present a novel automated classification method to be applied on these faults, which can be located on rigid pavement type. In order to collect proper representation of faults, a Kinect device was used, leading to three-dimensional point cloud structures. Images descriptors were used in order to establish the type of pothole and to get information regarding fault dimensions.
Rodrigo Huincalef, Guillermo Urrutia, Gabriel Ingravallo, Diego C. Martínez

Software Engineering

Frontmatter
White-Box Testing Framework for Object-Oriented Programming. An Approach Based on Message Sequence Specification and Aspect Oriented Programming
Abstract
The quality of software has become one of the most important factor in determining the success of products or enterprises. This paper presents a white-box testing framework for Object-Oriented Programming based on Message Sequence Specification and Aspect Oriented Programming. In the context of an Object-Oriented program, our framework can be used to test the correct order in which the methods of a class are invoked.
Martín L. Larrea, Juan Ignacio Rodríguez Silva, Matías N. Selzer, Dana K. Urribarri
Proposal for a Model of a Computer Systems Implantation Process (MoProIMP)
Abstract
From the analysis of software development methodologies, it was observed that many of them do not contemplate the process of system implantation or, if they do, they do not develop or manage them in a comprehensive manner.
As an answer to the identified gaps, MoProIMP, a model that allows to systematize the process of software implantation, is proposed. This model can be used together with the development methodology of the software producer organization.
MoProIMP identifies phases, activities, tasks (inputs and outputs) and existing dependencies in a software implantation, systematically managing each of them. Finally, a case study is presented as an initial validation to the proposed model.
Marisa Panizzi, Rodolfo Bertone, Alejandro Hossian
Storage Space Use in Mobile Applications
Abstract
The purpose of software development is meeting both functional and non-functional requirements. In mobile device applications, non-functional requirements are more relevant due to the restrictions inherent to these devices. One of these restrictions is the availability of limited storage space. Therefore, the size of a mobile application affects user preference for use. In this article, we assess how the choice of a mobile application development approach affects the final size of the application; we focus our analysis on text-, audio- and video-based applications and access to the camera in the device.
Juan Fernández Sosa, Pablo Thomas, Lisandro Delía, Germán Cáseres, Leonardo Corbalán, Fernando Tesone, Verena Olsowy
Scrum Towards IRAM-ISO 9001:2015. Integrating Documentation Required
Abstract
On the road to achieving good process quality management in software-developing small and medium enterprises, there is a lack of documentation in methodologies that are currently very widely used (such as Scrum). A proposal to adapt Scrum documentation and recommended IEEE standards for development process stages to the documentation required by IRAM-ISO 9001:2015, defining a single integrating document, is presented.
Julieta Calabrese, Silvia Esponda, Marcos Boracchia, Patricia Pesado

Databases and Data Mining

Frontmatter
Discovering Association Rules Using R. A Case Study on Retail’s Database
Abstract
Today, the high competitiveness in retail businesses requires them to seek new strategies to ensure their survival. To this end, organizations have understood that the data located in their transactional databases can be used as raw material to boost business growth, if they can be exploited properly. The research’s main objective is to apply Data Mining techniques for the discovery of association rules from purely commercial transactional data, taking as a study period 10-year in a household appliances and furniture retail entity. The selection’s phase and preparation data are described as well as its cost in man/hours. In the modeling phase, the Apriori and Eclat algorithms implemented in the arules package of the R tool were executed, where both the resulting associations and execution time were compared. The results show relevant patterns in the buying behavior of customers such as those that relate items and accessories’ prices.
Juan Manuel Báez Acuña, Clara Anuncia Paredes Cabañas, Gustavo Sosa-Cabrera, María E. García-Díaz
D3CAS: Distributed Clustering Algorithm Applied to Short-Text Stream Processing
Abstract
In this article, a proof of concept of a dynamic clustering algorithm based on density, called D3CAS, is presented. This algorithm was implemented to be run under the Spark Streaming framework, and it allows processing data streams. The algorithm was tested using a stream of short texts consisting of requirements generated by social media users, in particular, from a dataset called Pizza Request Dataset. The results, obtained in a virtualized environment, were analyzed with different configurations for algorithm parameters, which allowed establishing which are the configurations that yield the best results. Since the dataset used includes the label for each text in the stream, cluster purity could be measured and the results obtained could be compared to those presented by the authors of the dataset.
Roberto Molina, Waldo Hasperué, Augusto Villa Monte
Market Segmentation Using Data Mining Techniques in Social Networks
Abstract
Social networks have gained great popularity during the last decade, due to the advance of new technologies and people’s growing interest in generating content and sharing it with their contacts. This makes data generated in social networks grow exponentially over time.
These generated data contain information that can be analyzed, in order to discover patterns that can be of help in multiple disciplines. Marketing is one of these disciplines that is closely linked to understanding people’s behaviors, tendencies and tastes. The aim of this study is to apply data mining (DM) to discover patterns in data coming from social networks. Obtaining patterns will enable to carry out different types of segmentations to help the marketing professionals direct their campaigns.
Eduin Olarte, Marisa Panizzi, Rodolfo Bertone

Hardware Architectures, Networks, and Operating Systems

Frontmatter
Heuristic Variant for the Travelling Salesman Problem. Application Case: Sports Fishing Circuit
Abstract
The present work focuses on the construction of an algorithm to solve a sport fishing circuit, applying combinatorial optimization techniques in order to generate the best solution to the problem of the route for sport fishing in the province of Neuquén. The planning and management of roads for routes with preferences requires efficient systems for route optimization. Its complexity is exponential. For the resolution of this type of problems, heuristics must be used to allow feasible solutions. To model a tourist circuit associated with sport fishing, the exploration of a restricted graph is used. It is framed within the Travelling Salesman Problem. A metaheuristic Taboo search algorithm, based on a local search, is proposed to find a solution to the problem [1].
Ana Priscila Martínez, Lidia Marina López
Contention Analysis of Congestion Control Mechanisms in a Wireless Access Scenario
Abstract
Studying the interaction between two or more flows competing for shared resources in a network, has helped in the understanding of how the congestion control mechanisms of different TCP variants, interact with each other. In these cases, it’s essential to understand how such interactions come to be and to determine, under certain parameters, if it is possible for the flows to coexist in the same environment. On the other hand, it’s interesting to analyze the preponderance which one might have above the others, in reference to bandwidth usage. In this paper, these aspects are analyzed in order to establish how such coexistence could be achieved, determining in what way two data flows of TCP variants might achieve a balanced state in a channel. This is done considering that nowadays, most networks present scenarios with heterogeneous paths due to mixed technologies, meaning that one might find routes that use wired and wireless mediums.
Diego R. Rodríguez Herlein, Carlos A. Talay, Claudia N. González, Franco A. Trinidad, María L. Almada, Luis A. Marrone

Innovation in Software Systems

Frontmatter
Templates Framework for the Augmented Catalog System
Abstract
A novel system is presented for the augmentation of meta-contents, implemented over the existing virtual augmented catalog system (ACS), that shows positive results on improving the usability and lowering the entry barrier for non-expert users. It is introduced the concept of template of augmented reality, which allows the definition of amount and types of digital contents to be augmented together with their geometric transformations and visualization order. Once applied over a virtual catalog, the template helps to maintain a uniform format between its elements while simplifying the task for non-expert users by incorporating part of their domain vocabulary into the interface.
Nahuel Mangiarua, Jorge Ierache, Martin Becerra, Hernán Maurice, Santiago Igarza, Osvaldo Spositto
Smart Assistance Spots for the Blind or Visually Impaired People
Abstract
This paper describes the design and development of a system whose main purpose is to guide blind or visually impaired people through different environments in a city. The system consists in a mobile application that orients the user with audio messages and a set of geolocated electronic devices distributed at strategic points of an urban center. These electronic devices send environment information to the mobile app through wireless communication, providing accessibility and simplicity. A fully functional prototype was implemented, with a mobile application developed for Android and devices created on the Arduino platform.
Guillermo Arispe, Claudio Aciti, Matías Presso, José Marone

Signal Processing and Real-Time Systems

Frontmatter
Compound Interleaving Scheduling for SLM Transactions in Mode S Surveillance Radar
Abstract
Mode S Secondary Surveillance Radar establishes selective and univocally addressed transactions with aircrafts while possible using efficiently the available budgets of time. Obtaining the last benefit is key to supporting high-traffic density within a coverage. Compound methods including different interleaving algorithms for the scheduling of Short Length Message transactions are presented and tested under a heavy load simulated scenario.
Oscar Bria, Javier Giacomantone, Horacio Villagarcía Wanza
Position and Deformation-Checking Method Based on Structured Illumination. External Radiotherapy Use
Abstract
The main goal of a radiotherapy treatment is to provide the prescribed radiation dose to the tumor while minimizing healthy tissue irradiation. During every fraction of treatment, correct placement of the patient on the treatment couch as well as early detection of any shape changes that the patient´s body may undergo are crucial, because both affect the dose distribution. Structured illumination by fringe projection is typically used for finding an object’s spatial dimensions by projecting a pattern on it and taking a photo from a specific location. In this paper we propose a different approach for this technique: given an object’s 3D surface, an image can be computed and projected with the objective of locating this object at a specific location; only when the object is at the exact previously chosen position and preserves its original shape and form, an undistorted fringe pattern will be observed. Verification of patient’s correct position on the treatment couch and the detection of shape changes nearby the radiation field are feasible using the structured illumination based method presented in this work, a potentially useful tool for external radiotherapy treatments.
Leopoldo Garavaglia, Liliana Mairal, Jorge Runco

Computer Security

Frontmatter
Deep Convolutional Neural Networks for DGA Detection
Abstract
A Domain Generation Algorithm (DGA) is an algorithm to generate domain names in a deterministic but seemly random way. Malware use DGAs to generate the next domain to access the Command & Control (C&C) communication server. Given the simplicity of the generation process and speed at which the domains are generated, a fast and accurate detection method is required. Convolutional neural network (CNN) are well known for performing real-time detection in fields like image and video recognition. Therefore, they seemed suitable for DGA detection. The present work provides an analysis and comparison of the detection performance of a CNN for DGA detection. A CNN with a minimal architecture complexity was evaluated on a dataset with 51 DGA malware families and normal domains. Despite its simple architecture, the resulting CNN model correctly detected more than 97% of total DGA domains with a false positive rate close to 0.7%.
Carlos Catania, Sebastian García, Pablo Torres

Innovation in Computer Science Education

Frontmatter
Computer Science and Schools: A Specific Didactics?
Abstract
This paper presents the curricular proposal for the “Teaching Specialization in Computer Science Didactics” of the province of Buenos Aires, Argentina. The focus of this proposal is the training of high school teachers in the field of Computer Science, since there is a deficit in the training in this topic in compulsory school. The project arises in the framework of a call for national universities with Computer Science courses, launched by Fundación Sadosky of the Ministry of Science, Technology and Innovation. One of the main features is the acknowledgement of Higher Institutes for Teacher Training as referents of excellence in ongoing teacher training. The result is the consensual design and implementation, between these Institutes and the universities, of a curricular program of Computer Science.
Claudia Queiruga, Claudia Banchoff Tzancoff, Paula Venosa, Soledad Gómez, Glenda Morandi

Digital Governance and Smart Cities

Frontmatter
Open Government Assessment Models Applied to Province’s Capital Cities in Argentina and Municipalities in the Province of Buenos Aires
Abstract
With an increase of digital government policies and citizens that demand more of their governments, a new public management paradigm appeared, which became known as open government and is supported by three basic principles: Transparency, Collaboration and Participation. These are found in multiple different strategies, depending on the country, province or city adopting an open government, but all of them sharing two common pillars: open public data and open processes. Lately, various initiatives were promoted on various government levels to allow all citizens to have access to public information.
In this context, this document proposes an assessment model to establish the progress made towards that goal in the capital cities of the different provinces of Argentina and a select group of municipalities in the province of Buenos Aires through the various open government tools offered to citizens by such cities through their official websites to improve their services.
Ariel Pasini, Juan Santiago Preisegger, Patricia Pesado
Combining Artificial Intelligence Services for the Recognition of Flora Photographs: Uses in Augmented Reality and Tourism
Abstract
Tourism information services are evolving rapidly. With Internet, tourists organize their trips by managing information before arriving at their destination. Nature is the main tourist attraction in Argentina. However, the information tools as field guides, have had few improvements in their digital version compared to printed ones. This work compares and combines machine learning services that includes deep learning, artificial intelligence and image recognition, to evaluate the app development for mobile phones that offer recognition of flora species in real time, in natural areas with low or no internet connectivity. Recognition of three Nothofagus tree species (with a dataset of 45 photos per species) were evaluated in the Tierra del Fuego National Park, using IBM Watson, Google Cloud and Microsoft Azure. Finally, we defined an algorithm combining those services to improve the results. Google Cloud was the service with the best performance recognizing all the tree species (83% effectiveness in average). The accuracy of Watson and Azure was lower than Google Cloud, and varied according to tree species. Combined algorithm improved the recognition with a 90% effectiveness in average. A next iteration of this work expects to increase the accuracy of recognition to get a total of 150 photos per specie into the dataset. We also expect to use assisted learning to improve the efficiency of the neural network obtained to know the adaptation capacities for each evaluated service.
Guillermo Feierherd, Federico González, Leonel Viera, Rosina Soler, Lucas Romano, Lisandro Delía, Beatriz Depetris
Backmatter
Metadata
Title
Computer Science – CACIC 2018
Editors
Patricia Pesado
Claudio Aciti
Copyright Year
2019
Electronic ISBN
978-3-030-20787-8
Print ISBN
978-3-030-20786-1
DOI
https://doi.org/10.1007/978-3-030-20787-8

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