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Scenario: The particulate matter (PM) is associated with all particles (solid and liquid) suspended in the air. Depending on the kind and size of the particle, each one represents different kinds of risks for human health. The emerging of tiny, available, and accessible devices related to the Internet-of-Things (IoT) has allowed the implementation of different monitoring strategies. Objective: To identify and characterize the IoT-based Real-time monitoring strategies which have implemented a measurement process to study the effect of the PM on human health. Methodology: A wide analysis based on the Systematic Mapping Study (SMS) was performed on September 4 of 2020. The ACM, IEEE, ScienceDirect, SpringerLink, Scopus, and Wiley databases were considered in the exploration. Results: 48 articles addressing the IoT-based PM measurement were obtained, falling them between 2010 and 2020 with growing up interest. The main use of this technology is related to increase the coverage and density of environmental monitoring stations due to the impact of PM on human health. Also, approaches to monitoring air quality and their potential effects on people’s affections are described. Conclusions: Collaborative, People-aware, Global proposals tend to get increasing interest. Only 6 (12.5%) articles incorporated some recommendation system based on PM measures. The accuracy and precision are the main concern around low-cost sensors for measuring PM. Thus, the calibration process is highlighted in 64.44% of articles. The main challenges reside in a combination of uncertainties in PM measurement, health impacts, data quality, and the influence of environmental variables on all of them.
Mario J. Divan; Maria Laura Sanchez-Reynoso; Juan Esteban Panebianco; Mariano J. Mendez. IoT-Based Approaches for Monitoring the Particulate Matter and Its Impact on Health. IEEE Internet of Things Journal 2021, 8, 11983 -12003.
AMA StyleMario J. Divan, Maria Laura Sanchez-Reynoso, Juan Esteban Panebianco, Mariano J. Mendez. IoT-Based Approaches for Monitoring the Particulate Matter and Its Impact on Health. IEEE Internet of Things Journal. 2021; 8 (15):11983-12003.
Chicago/Turabian StyleMario J. Divan; Maria Laura Sanchez-Reynoso; Juan Esteban Panebianco; Mariano J. Mendez. 2021. "IoT-Based Approaches for Monitoring the Particulate Matter and Its Impact on Health." IEEE Internet of Things Journal 8, no. 15: 11983-12003.
The Data Stream Processing Strategy (DSPS) is focused on the automatization of measurement projects based on a measurement framework. The measurement adapter (MA) is an architecture component located on mobile devices aims to integrate heterogeneous data sources (i.e., sensors). The Gathering Function (GF) is the component responsible for interacting and receiving measures from the MAs, and it resides on the Stream Processing Engine (SPE). MA and GF share the project definition based on a measurement framework to foster data interoperability, while MA regulates the frequency, size, and route related to data transmission. As contributions (i) The brief data message is introduced to optimize the data transmission keeping immutable the hierarchical data organization based on the project definition, and (ii) The integrity record for mobile and SPE environments is described based on a Merkle Tree. This allows optimizing each data transaction, incorporating a historical integrity record both MA and SPE. The proposals and simulations have been implemented on the cincamimis, cincamipd, mair, and pabmmcommons libraries, which are freely available on GitHub under the terms of the Apache 2.0 licence. Four simulations are explained to detail how to measures were obtained. Interesting results show that the brief data message consumes 17.50 KB to transmit 1000 measures (2.4 times smaller than JSON), while a message with 200 measures could be generated and compressed using GZIP in 25.12 ms (2.43 times faster than JSON). 196 KB is required to keep 17 min of the integrity history in a MA, being created in 4.85 ms.
Mario José Diván; María Laura Sánchez-Reynoso. Metadata-based measurements transmission verified by a Merkle Tree. Knowledge-Based Systems 2021, 219, 106871 .
AMA StyleMario José Diván, María Laura Sánchez-Reynoso. Metadata-based measurements transmission verified by a Merkle Tree. Knowledge-Based Systems. 2021; 219 ():106871.
Chicago/Turabian StyleMario José Diván; María Laura Sánchez-Reynoso. 2021. "Metadata-based measurements transmission verified by a Merkle Tree." Knowledge-Based Systems 219, no. : 106871.
An intelligent system is a technology that has opened diverse ranges of possibilities due to its availability, value, and accessibility. Such an intelligence resides in the possibility to measure and know the current state of entities or environments. Thus, the measurement process constitutes a key asset for many aspects related to the intelligence of systems (e.g., decision-making) and the relationship with the data gathering strategies. A strategy for formalizing monitoring projects based on entity states and scenarios is introduced. It integrates the visualization pipeline to align the visual communication to measurement requirements. From the methodological point of view, an extension of a measurement and evaluation framework which supports the modeling of entity states and scenarios is considered. The framework allows agreeing on concepts required to formalize a measurement project. Thus, a specialization of the Goal-oriented Context-aware Measurement and Evaluation strategy is introduced using the business process model to describe how scenarios and entity states are articulated jointly with their transition models. Also, the visualization pipeline is integrated into the new strategy to articulate the information need that gives origin to the measurement project jointly with the visual communication strategy. A synthesized case as a proof-of-concept is introduced. In this way, a monitoring strategy aware of scenarios, entity states, and the visualization pipeline into a measurement project is reached. Thus, traceability about each visual perspective is aligned with measurement points of view.
Mario José Diván; Madhusudan Singh. The Impact of the Measurement Process in Intelligent System of Data Gathering Strategies. Transactions on Petri Nets and Other Models of Concurrency XV 2021, 445 -457.
AMA StyleMario José Diván, Madhusudan Singh. The Impact of the Measurement Process in Intelligent System of Data Gathering Strategies. Transactions on Petri Nets and Other Models of Concurrency XV. 2021; ():445-457.
Chicago/Turabian StyleMario José Diván; Madhusudan Singh. 2021. "The Impact of the Measurement Process in Intelligent System of Data Gathering Strategies." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 445-457.
The detection and evaluation of semantically similar entities in measurement projects is a key asset for real-time decision making because it allows reusing their knowledge and previous experiences. In this way, the objective of this work is to map the thematic area of data stream processing to identify the topics that have been investigated in the detection of semantically similar entities. From the methodological point of view, a systematic mapping study was conducted obtaining 2,122 articles. Thus, 111 were kept refining the search strategy, and 25 were considered once the filters were applied jointly with the inclusion/exclusion criteria. After reading the 25 documents, just 6 were pertinent and allowed answering the research questions aligned with the research objective. The semantic similarity applied to entities under monitoring in the measurement and evaluation projects is a challenge. Real-time decision making depends on the obtained measures, the monitored entity, and the context in which it is immersed.
María Laura Sánchez Reynoso; Mario José Diván. Assessment of semantic similarity in entities under monitoring: A systematic literature mapping. Revista Facultad de Ingeniería Universidad de Antioquia 2020, 21 -31.
AMA StyleMaría Laura Sánchez Reynoso, Mario José Diván. Assessment of semantic similarity in entities under monitoring: A systematic literature mapping. Revista Facultad de Ingeniería Universidad de Antioquia. 2020; (99):21-31.
Chicago/Turabian StyleMaría Laura Sánchez Reynoso; Mario José Diván. 2020. "Assessment of semantic similarity in entities under monitoring: A systematic literature mapping." Revista Facultad de Ingeniería Universidad de Antioquia , no. 99: 21-31.
Data constitute the raw material of any kind of processing strategy and the core elements from the statistical learning viewpoint. The key aspect is how a data processor or algorithm could capture the essence of the data meaning for discriminating their behaviors based on their semantic. In this complexity, the data stream processing incorporates an additional concern because it implies that the data are processed homogeneously with the origin (i.e. without any modification), just using the available hardware resources at the moment in which they arrive. The real-time decision making tends to be a constant functionality in each data stream processing engine, be it through the incremental decision trees, cluster analysis, among others. In this chapter, a systematic literature mapping is carried forward with the aim of mapping strategies that allow discriminating the data meanings and use them for guiding the processing in the data stream context. The method used is the systematic mapping study, through which the Scopus database is explored and analyzed following the filters which limiting the specific field and inclusion/exclusion criteria. The data semantics, the effect in the data processing, and the impact in the online decision making are here dimensioned from the research viewpoint. Finally, the different strategies for managing the data meaning and its impact on real-time data processing are outlined, dimensioned, compared, and classified.
Mario José Diván; María Laura Sánchez-Reynoso. Managing the Data Meaning in the Data Stream Processing: A Systematic Literature Mapping. Algorithms for Intelligent Systems 2020, 31 -46.
AMA StyleMario José Diván, María Laura Sánchez-Reynoso. Managing the Data Meaning in the Data Stream Processing: A Systematic Literature Mapping. Algorithms for Intelligent Systems. 2020; ():31-46.
Chicago/Turabian StyleMario José Diván; María Laura Sánchez-Reynoso. 2020. "Managing the Data Meaning in the Data Stream Processing: A Systematic Literature Mapping." Algorithms for Intelligent Systems , no. : 31-46.
Mario José Diván; María L. Sánchez Reynoso; Mohd Helmy Abd Wahab. Dynamic Switching in the Measurements’ Collecting from Heterogeneous Data Sources. Journal of Physics: Conference Series 2020, 1529, 1 .
AMA StyleMario José Diván, María L. Sánchez Reynoso, Mohd Helmy Abd Wahab. Dynamic Switching in the Measurements’ Collecting from Heterogeneous Data Sources. Journal of Physics: Conference Series. 2020; 1529 ():1.
Chicago/Turabian StyleMario José Diván; María L. Sánchez Reynoso; Mohd Helmy Abd Wahab. 2020. "Dynamic Switching in the Measurements’ Collecting from Heterogeneous Data Sources." Journal of Physics: Conference Series 1529, no. : 1.
Nowadays, data are generated both by users and other systems deriving new data from the previous ones for supporting decision making. The Electronic Health Records contains from structured data (e.g. hospital id, etc.), semi-structured data (e.g. a Health Level Seven-based records), to unstructured data (e.g. patient’s symptoms). The big challenge with health in smart cities is associated with the prevention, both the business and human health point of view. That is to say, avoid the propagation of certain diseases’ patterns is the best option no just for people, but also from the city’s health and the local economy. Thus, an architecture able to integrate into an Organizational Memory the medical data coming from heterogeneous repositories with the aim of gathering different kinds of symptoms is introduced. The query in the architecture is understood such as an unstructured text (i.e. symptoms) or an electronic health record. In this sense, the architecture is able to reach similar cases from the organizational memory based on a textual similarity analysis for limiting the search space. Next, using the International Classification of Diseases is possible to convert a case to a vector model representation in order to compute metric distances and get other cases order by a level of similarity. Each query answer contains a set of recommendations based on the frequency of diagnoses related to similar cases are given in order to share previous experiences. The processes point of view related to architecture is outlined. Finally, some conclusions and future works are outlined.
Valerio Frittelli; Mario José Diván. An Architecture for e-Health Recommender Systems Based on Similarity of Patients’ Symptoms. Blockchain Technology for IoT Applications 2020, 155 -180.
AMA StyleValerio Frittelli, Mario José Diván. An Architecture for e-Health Recommender Systems Based on Similarity of Patients’ Symptoms. Blockchain Technology for IoT Applications. 2020; ():155-180.
Chicago/Turabian StyleValerio Frittelli; Mario José Diván. 2020. "An Architecture for e-Health Recommender Systems Based on Similarity of Patients’ Symptoms." Blockchain Technology for IoT Applications , no. : 155-180.
Vijander Singh; Sandeep Kumar; Ramesh C. Poonia; Linesh Raja; Mario José Diván; Amar Patnaik; Pranav Dass; Ravi Shanker Dubey. Guest Editors. Journal of Interdisciplinary Mathematics 2020, 23, 1 .
AMA StyleVijander Singh, Sandeep Kumar, Ramesh C. Poonia, Linesh Raja, Mario José Diván, Amar Patnaik, Pranav Dass, Ravi Shanker Dubey. Guest Editors. Journal of Interdisciplinary Mathematics. 2020; 23 (1):1.
Chicago/Turabian StyleVijander Singh; Sandeep Kumar; Ramesh C. Poonia; Linesh Raja; Mario José Diván; Amar Patnaik; Pranav Dass; Ravi Shanker Dubey. 2020. "Guest Editors." Journal of Interdisciplinary Mathematics 23, no. 1: 1.
Most enterprises host their critical data in data centers to have a secure, robust environment supporting the highest uptime for their IT operations. As per industry best practices, standards, conference papers and journals; there are various ways suggested through which efficiency of data center is calculated. This review paper provides information on the efficiency calculation factors relatum to data center loads and its classification. It describes how measurement of data center efficiency is to be done and which are the crucial components which need to be considered for calculating the true values accurately for power usage efficiency (PUE) and data center infrastructure efficiency (DCiE).Basis on researchfindings & working towards data center efficiency measurement, the future research scope has been identified that how various techniques can be applied on data center major components - Power & Cooling which further can be helpful towards improvement of Data Center efficiency.
Rajendra Kumar; Sunil Kumar Khatri; Mario José Diván. Efficiency measurement of data centers: An elucidative review. Journal of Discrete Mathematical Sciences and Cryptography 2020, 23, 221 -236.
AMA StyleRajendra Kumar, Sunil Kumar Khatri, Mario José Diván. Efficiency measurement of data centers: An elucidative review. Journal of Discrete Mathematical Sciences and Cryptography. 2020; 23 (1):221-236.
Chicago/Turabian StyleRajendra Kumar; Sunil Kumar Khatri; Mario José Diván. 2020. "Efficiency measurement of data centers: An elucidative review." Journal of Discrete Mathematical Sciences and Cryptography 23, no. 1: 221-236.
Vijander Singh; Sandeep Kumar; Ramesh Chandra Poonia; Linesh Raja; Mario José Diván; Amar Patnaik; Pranav Dass; Ravi Shanker Dubey. Foreword. Journal of Interdisciplinary Mathematics 2020, 23, 1 .
AMA StyleVijander Singh, Sandeep Kumar, Ramesh Chandra Poonia, Linesh Raja, Mario José Diván, Amar Patnaik, Pranav Dass, Ravi Shanker Dubey. Foreword. Journal of Interdisciplinary Mathematics. 2020; 23 (1):1.
Chicago/Turabian StyleVijander Singh; Sandeep Kumar; Ramesh Chandra Poonia; Linesh Raja; Mario José Diván; Amar Patnaik; Pranav Dass; Ravi Shanker Dubey. 2020. "Foreword." Journal of Interdisciplinary Mathematics 23, no. 1: 1.
Mario José Diván; María Laura Sánchez-Reynoso. The impact of Internet of Things and data semantics on decision making for outpatient monitoring. Computational Intelligence and Its Applications in Healthcare 2020, 1 -15.
AMA StyleMario José Diván, María Laura Sánchez-Reynoso. The impact of Internet of Things and data semantics on decision making for outpatient monitoring. Computational Intelligence and Its Applications in Healthcare. 2020; ():1-15.
Chicago/Turabian StyleMario José Diván; María Laura Sánchez-Reynoso. 2020. "The impact of Internet of Things and data semantics on decision making for outpatient monitoring." Computational Intelligence and Its Applications in Healthcare , no. : 1-15.
N. Yuvaraj; R. Arshath Raja; N.V. Kousik; Prashant Johri; Mario José Diván. Analysis on the prediction of central line-associated bloodstream infections (CLABSI) using deep neural network classification. Computational Intelligence and Its Applications in Healthcare 2020, 229 -244.
AMA StyleN. Yuvaraj, R. Arshath Raja, N.V. Kousik, Prashant Johri, Mario José Diván. Analysis on the prediction of central line-associated bloodstream infections (CLABSI) using deep neural network classification. Computational Intelligence and Its Applications in Healthcare. 2020; ():229-244.
Chicago/Turabian StyleN. Yuvaraj; R. Arshath Raja; N.V. Kousik; Prashant Johri; Mario José Diván. 2020. "Analysis on the prediction of central line-associated bloodstream infections (CLABSI) using deep neural network classification." Computational Intelligence and Its Applications in Healthcare , no. : 229-244.
Nowadays, the data has a dynamic never seen before. They have continuous growth which is associated with the permanent generation from both data entered by users and new data derived from systems. In this context, the data visualization plays a highlighted role because it allows synthetically communicating high-data volume making them understandable for the End-user. This aspect constitutes a key asset throughout the decision-making process in any organization because incorporates dynamism and fosters different kinds of analysis. For that reason, the use of guidelines allows tutoring a process and in particular, those related to data visualizations. In this work, the general visualization process is described in order to schematize the way in which user requirements and sketches converge. Next, the visualization design describes the way in which the sketches could be implemented using the software. As a contribution, here an application case using the forest’s fires dataset of Argentina between 2011 and 2017 is shown in order to serve as a reference for the guidelines’ using. The case was implemented using Qlik Sense Cloud, incorporating a set of dynamic behaviors included in the platform, such as the possibility of making zoom on maps or sharing the selections between visual components. The employed data are freely available on datos.gob.ar, the Open-data platform of Argentina’s Government. The case allows exemplifying the use of guidelines, its applicability, and the chosen data visualization strategy in a consistent way.
Maria Laura Sanchez Reynoso; Mario José Diván. Applying Data Visualization Guideline on Forest Fires in Argentina. 2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) 2020, 617 -622.
AMA StyleMaria Laura Sanchez Reynoso, Mario José Diván. Applying Data Visualization Guideline on Forest Fires in Argentina. 2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence). 2020; ():617-622.
Chicago/Turabian StyleMaria Laura Sanchez Reynoso; Mario José Diván. 2020. "Applying Data Visualization Guideline on Forest Fires in Argentina." 2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence) , no. : 617-622.
The processing strategy based on measurement metadata is a data stream engine running on Apache Storm, who is able to process measures in real-time. In the data stream context, the data have no an associated limit, they are al-ways arriving. The Attribute-Relation File Format (ARFF) is used by popular software like Weka, allowing offline analysis in the machine learning and data mining area. However, the ARFF file has a finite size. The CincamimisConversor library allows exporting from the data streams organized under a measurement interchange schema to a columnar-data organization in real-time. Here, an extension to the library is introduced for supporting the real-time translating and storing from the heterogeneous data streams to the ARFF file format. This is very useful, because through the library now is possible to collect data from heterogeneous data sources (e.g. Internet-of-Thing-IoT-devices) and export them in real-time for offline analysis in Weka. Even, this could foster a lot of educational applications among IoT, the measurement process with heterogeneous sources, data stream processing strategy, and Weka. A discrete simulation was carried out, obtaining promising results. It is just required at most 0.2387 ms for translating 5000 measures, while the storing operation for them consumed less than 0.2028 ms on a Solid-State disk.
Mario José Diván; María Laura Sánchez Reynoso. Articulating heterogeneous data streams with the attribute-relation file format. ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING: FROM THEORY TO APPLICATIONS (SERIES 2): Proceedings of the International Conference of Electrical and Electronic Engineering (ICon3E 2019) 2019, 2173, 020021 .
AMA StyleMario José Diván, María Laura Sánchez Reynoso. Articulating heterogeneous data streams with the attribute-relation file format. ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING: FROM THEORY TO APPLICATIONS (SERIES 2): Proceedings of the International Conference of Electrical and Electronic Engineering (ICon3E 2019). 2019; 2173 (1):020021.
Chicago/Turabian StyleMario José Diván; María Laura Sánchez Reynoso. 2019. "Articulating heterogeneous data streams with the attribute-relation file format." ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING: FROM THEORY TO APPLICATIONS (SERIES 2): Proceedings of the International Conference of Electrical and Electronic Engineering (ICon3E 2019) 2173, no. 1: 020021.
The open government platforms allow the governments centralize and share different kinds of datasets useful for making transparent public management. The data in this kind of platforms are shared in different formats, but mainly in tabular data formats, oriented to facilitate its download and use by any citizen. The government of Argentina developed datos.gob.ar, which is a platform able to centralize the official datasets from different public organisms. In this work, the official advertising's distribution was chosen for analyzing its structure and meaning with the aim of showing that the data understandability is not reached by citizens through direct reading. As contributions, a complementary tool for fostering the communication of the public data by mean of an associative application based on visualization is proposed. In addition, a survey on students belonging to the first year of the public accountant career was driven with the aim of evaluating the perception between the open-data raw datasets in contrast with the same visually communicated data. Even when 70.2% of students knew the datos.gob.ar platform, the 69% did not know its aim. Finally, the associated risks with predictions which emerge from the effect of the data meaning, structure, and its usefulness are exemplified through temporal series applied to the official advertising's distribution.
Maria Laura Sanchez Reynoso; Mario José Diván. Contributions to the Communication of the Official Advertising's Distribution in Argentina. 2019 4th International Conference on Information Systems and Computer Networks (ISCON) 2019, 508 -513.
AMA StyleMaria Laura Sanchez Reynoso, Mario José Diván. Contributions to the Communication of the Official Advertising's Distribution in Argentina. 2019 4th International Conference on Information Systems and Computer Networks (ISCON). 2019; ():508-513.
Chicago/Turabian StyleMaria Laura Sanchez Reynoso; Mario José Diván. 2019. "Contributions to the Communication of the Official Advertising's Distribution in Argentina." 2019 4th International Conference on Information Systems and Computer Networks (ISCON) , no. : 508-513.
Maria Laura Sanchez-Reynoso; Mario José Diván. A Systematic Literature Mapping on the Similar Semantically Entities in Measurement Projects. 2019 International Conference on Virtual Reality and Visualization (ICVRV) 2019, 1 .
AMA StyleMaria Laura Sanchez-Reynoso, Mario José Diván. A Systematic Literature Mapping on the Similar Semantically Entities in Measurement Projects. 2019 International Conference on Virtual Reality and Visualization (ICVRV). 2019; ():1.
Chicago/Turabian StyleMaria Laura Sanchez-Reynoso; Mario José Diván. 2019. "A Systematic Literature Mapping on the Similar Semantically Entities in Measurement Projects." 2019 International Conference on Virtual Reality and Visualization (ICVRV) , no. : 1.
Mario José Diván. Towards a Stratified Multi-Criteria Decision-Making in the Real-Time Data Processing. 2019 International Conference on Virtual Reality and Visualization (ICVRV) 2019, 1 .
AMA StyleMario José Diván. Towards a Stratified Multi-Criteria Decision-Making in the Real-Time Data Processing. 2019 International Conference on Virtual Reality and Visualization (ICVRV). 2019; ():1.
Chicago/Turabian StyleMario José Diván. 2019. "Towards a Stratified Multi-Criteria Decision-Making in the Real-Time Data Processing." 2019 International Conference on Virtual Reality and Visualization (ICVRV) , no. : 1.
The dynamism of the economies requires updated data when decisions must be made. Currently, the Internet-of-Things incorporates a lot of different tiny and low-cost electronic devices able to be used for implementing a measurement process. However, those data sources are heterogeneous. The Data Stream Processing Architecture (DSPA) uses a Measurement and Evaluation (M&E) framework for warrantying the repeatability and consistency in the measurement process, jointly with the comparability of their results. The data arrive from the heterogeneous data sources to DSPA organized under the Measurement Interchange Schema (MIS), which is based on the project definition and allows matching each concept under monitoring with the corresponding measure from each device. Because the metric (or variable) related to each entity under monitoring should be analyzed in its own context and considering that data continuously arriving, a new strategy related to sliding logical windows is incorporated into the PAbMM_Win library, fostering processing alternatives jointly with the data interchange. Thus, the concepts of Layers and Carriers are introduced. On the one hand, the layers abstract the data processing from the logical viewpoint using the measurement project definition. On the other hand, the carriers allow transporting interpreted data to external data processing platforms in a transparent way. Its internal organization is here described. A discrete simulation shows its associated processing times. A snapshot on a whole measurement project could be taken and transported to a thirds' platform in only 16.72 ms with 1000 measures.
Mario Divan. A Real-Time Data Processing based on Multilayer Windows and the Measurement Interchange Schema. 2019 4th International Conference on Information Systems and Computer Networks (ISCON) 2019, 757 -762.
AMA StyleMario Divan. A Real-Time Data Processing based on Multilayer Windows and the Measurement Interchange Schema. 2019 4th International Conference on Information Systems and Computer Networks (ISCON). 2019; ():757-762.
Chicago/Turabian StyleMario Divan. 2019. "A Real-Time Data Processing based on Multilayer Windows and the Measurement Interchange Schema." 2019 4th International Conference on Information Systems and Computer Networks (ISCON) , no. : 757-762.
The genre violence constitutes a social scourge which has broad effects in the social nucleus. This kind of issues affect in a direct way to women but also all the dependents. Sadly, this scourge does not respect any kind of age, being present both young and elderly women. The complexity of the generated situation impacts in the present, but also could leave permanent marks in the involved persons. Under the umbrella of a legal agreement with the Government of Jujuy, this work analyzes real data based on the victims' complaints between 2014 and 2017. The situation related to genre violence in the province of Jujuy is synthesized, putting in context the national normative. The data source structure is introduced jointly with its elemental issues and main variables. The correlation between victims' ages and victimizers' ages is introduced. The data were pre-processed for solving aspects related to the absence of values and the coding of ordinal variables. The K-means algorithm was used on the preprocessed genre violence records obtaining nine groups with its corresponding characteristics. The main contribution is the detection of the nine groups and its characterization, which constitute an initial approach to patterns of the committed crimes by genre violence in Jujuy between 2014 and 2017. This is useful feedback for the prevention organisms in which the agreement is incorporated.
Alejandra Ivone Arias; Mario José Diván. Contributions to the Genre Violence Analysis in Jujuy: Initial Characterization of Crimes. 2019 4th International Conference on Information Systems and Computer Networks (ISCON) 2019, 514 -519.
AMA StyleAlejandra Ivone Arias, Mario José Diván. Contributions to the Genre Violence Analysis in Jujuy: Initial Characterization of Crimes. 2019 4th International Conference on Information Systems and Computer Networks (ISCON). 2019; ():514-519.
Chicago/Turabian StyleAlejandra Ivone Arias; Mario José Diván. 2019. "Contributions to the Genre Violence Analysis in Jujuy: Initial Characterization of Crimes." 2019 4th International Conference on Information Systems and Computer Networks (ISCON) , no. : 514-519.
The real-time data processing is becoming a key aspect in relation to the Internet of things (IoT) applications. The IoT is characterized by the heterogeneity of the devices, and for that reason, the data providing rate of each one is variable and unpredictable. Because the data arriving rate from the data sources could exceed the data processing rate, the use of the load-shedding techniques is necessary. The metadata-guided processing strategy is a real-time data processing schema which the project definitions are based on a framework. Here, a new load-shedding technique based on the measurement project definition is introduced. This allows balancing between the data variability and the priority, retaining the important data based on the expert’s knowledge from the project definition and the variations of the data series related to each metric.
Mario José Diván; María Laura Sánchez Reynoso. A Load-Shedding Technique Based on the Measurement Project Definition. Advances in Intelligent Systems and Computing 2019, 1027 -1033.
AMA StyleMario José Diván, María Laura Sánchez Reynoso. A Load-Shedding Technique Based on the Measurement Project Definition. Advances in Intelligent Systems and Computing. 2019; ():1027-1033.
Chicago/Turabian StyleMario José Diván; María Laura Sánchez Reynoso. 2019. "A Load-Shedding Technique Based on the Measurement Project Definition." Advances in Intelligent Systems and Computing , no. : 1027-1033.