Role of Machine Learning, Deep Learning and WSN in Disaster Management: A Review and Proposed Architecture

Disasters are occurrences that have the potential to adversely affect a community via casualties, ecological damage, or monetary losses. Due to its distinctive geoclimatic characteristics, India has always been susceptible to natural calamities. Disaster Management is the management of disaster prevention, readiness, response, and recovery tasks in a systematic manner. This paper reviews various types of disasters and their management approaches implemented by researchers using Wireless Sensor Networks (WSNs) and machine learning techniques. It also compares and contrasts various prediction algorithms and uses the optimal algorithm on multiple flood prediction datasets. After understanding the drawbacks of existing datasets, authors have developed a new dataset for Mumbai, Maharashtra consisting of various attributes for flood prediction. The performance of the optimal algorithm on the dataset is seen by the training, validation and testing accuracy of 100%, 98.57% and 77.59% respectively

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Human-Computer Interaction: Security Aspects

Along with the rapid development of intelligent information age, users are having a growing interaction with smart devices. Such smart devices are interconnected together in the Internet of Things (IoT). The sensors of IoT devices collect information about users' behaviors from the interaction between users and devices. Since users interact with IoT smart devices for the daily communication and social network activities, such interaction generates a huge amount of network traffic. Hence, users' behaviors are playing an important role in the security of IoT smart devices, and the security aspects of Human-Computer Interaction are becoming significant. In this dissertation, we provide a threefold contribution: (1) we review security challenges of HCI-based authentication, and design a tool to detect deceitful users via keystroke dynamics; (2) we present the impact of users' behaviors on network traffic, and propose a framework to manage such network traffic; (3) we illustrate a proposal for energy-constrained IoT smart devices to be resilient against energy attack and efficient in network communication. More in detail, in the first part of this thesis, we investigate how users' behaviors impact on the way they interact with a device. Then we review the work related to security challenges of HCI-based authentication on smartphones, and Brain-Computer Interfaces (BCI). Moreover, we design a tool to assess the truthfulness of the information that users input using a computer keyboard. This tool is based on keystroke dynamics and it relies on machine learning technique to achieve this goal. To the best of our knowledge, this is the first work that associates the typing users' behaviors with the production of deceptive personal information. We reached an overall accuracy of 76% in the classification of a single answer as truthful or deceptive. In the second part of this thesis, we review the analysis of network traffic, especially related to the interaction between mobile devices and users. Since the interaction generates a huge amount of network traffic, we propose an innovative framework, GolfEngine, to manage and control the impact of users behavior on the network relying on Software Defined Networking (SDN) techniques. GolfEngine provides users a tool to build their security applications and offers Graphical User Interface (GUI) for managing and monitoring the network. In particular, GolfEngine provides the function of checking policy conflicts when users design security applications and the mechanism to check data storage redundancy. GolfEngine not only prevents the malicious inputting policies but also it enforces the security about network management of network traffic. The results of our simulation underline that GolfEngine provides an efficient, secure, and robust performance for managing network traffic via SDN. In the third and last part of this dissertation, we analyze the security aspects of battery-equipped IoT devices from the energy consumption perspective. Although most of the energy consumption of IoT devices is due to user interaction, there is still a significant amount of energy consumed by point-to-point communication and IoT network management. In this scenario, an adversary may hijack an IoT device and conduct a Denial of Service attack (DoS) that aims to run out batteries of other devices. Therefore, we propose EnergIoT, a novel method based on energetic policies that prevent such attacks and, at the same time, optimizes the communication between users and IoT devices, and extends the lifetime of the network. EnergIoT relies on a hierarchical clustering approach, based on different duty cycle ratios, to maximize network lifetime of energy-constrained smart devices. The results show that EnergIoT enhances the security and improves the network lifetime by 32%, compared to the earlier used approach, without sacrificing the network performance (i.e., end-to-end delay)

Relações entre iniciação científica e aspectos socioeducacionais, acadêmicos e profissionais de egressos da Universidade Federal do Paraná

Orientador: Prof. Dr. Cícero Aparecido BezerraCoorientadora: Prof.ª Dr.ª Rafaela Mantovani FontanaTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Sociais Aplicadas, Programa de Pós-Graduação em Gestão da Informação. Defesa : Curitiba, 04/05/2022Inclui referênciasResumo: A Iniciação Científica (IC) propicia o contato prematuro de discentes com o ambiente científico das universidades e possui papel estratégico na formação de alunos e na renovação de recursos humanos qualificados, seja para a pesquisa ou mesmo para o mercado de trabalho. Esta tese tem como objetivo analisar alunos egressos da Universidade Federal do Paraná (UFPR) entre os anos de 2005 a 2020, considerando caracerísticas dos escopos socioeducacional, acadêmico, científico e profissional, estabelecendo comparações e verificando diferenças conforme a participação na atividade de IC. Parte-se do pressuposto que a IC não exerce diferença na vida profissional do estudante, limitando os ganhos da atividade para a área científica, com ingresso na pós-graduação e publicação de artigos. Metodologicamente, o estudo possui natureza quantitativa, com dados coletados de múltiplas fontes. Informações socioeducacionais, acadêmicas e de participações em IC foram obtidas das próprias bases da UFPR - Sistema Integrado de Ensino (SEI), Núcleo de Concursos (NC) e Sistema de Iniciação Científica e Tecnológica (SICT). Para informações científicas de ingresso em pós-graduação e publicações, foram colhidos dados da plataforma Currículo Lattes, enquanto os dados profissionais foram selecionados da Relação Anual de Informações Sociais (RAIS). Para atingir o objetivo do estudo, técnicas estatísticas bivariadas e análise de correspondência múltipla foram empregadas em 37.516 egressos da UFPR - 8.133 com IC, 29.383 sem IC - de modo a identificar as características e diferenças entre os grupos IC x Sem IC, e validar protocolo de pesquisa e tese apresentadas. Os resultados apontaram que: i) no escopo socioeducacional, egressos que participaram da IC foram ligeiramente mais jovens; predominantemente do sexo feminino; demonstraram menor interesse em participar de atividades profissionais em tempo integral durante o curso; e apresentaram melhor desempenho no vestibular; não houve qualquer diferença para variáveis de cota ou raça; ii) no âmbito acadêmico, egressos com IC possuíram carga horária do curso maior; estiveram associados a cursos do turno matutino; e figuraram de maneira mais intensa nas áreas de Ciências Sociais Aplicadas e Ciências da Saúde; e também apresentaram maior índice de rendimento acadêmico; ii) no escopo científico, os egressos com IC apresentaram maior encaminhamento para cursos de pós-graduação stricto sensu e lato sensu, e médias maiores para todas as variáveis de publicações analisadas, tanto durante a graduação como após este período; iv) nas variáveis profissionais, houve maior empregabilidade ao longo dos anos para egressos sem IC; ao observar a empregabilidade para a área de docência, os percentuais foram maiores para os alunos IC; em todas as variáveis envolvendo a remuneração, não houve padrão que pudesse postar um grupo de maneira favorável ou mesmo de destaque em relação ao outro. Os resultados fortalecem a ideia de que os benefícios propiciados pela IC se encontram principalmente para a área científica dos estudantes egressos, com destaque no encaminhamento para a pós-graduação e publicações.Abstract: Undergraduate Research (UR) provides early contact of the students with the scientific environment of the universities and plays a strategic role in the training of students and the renewal of qualified human resources, whether for research or even for the labor market. This thesis aims to analyze students from the Federal University of Parana (UFPR) between the years 2005 to 2020, considering characteristics of the socio-educational, academic, scientific and professional scopes, establishing comparisons and verifying differences according to the participation in the UR activity. It is assumed that UR makes no difference in the student's academic and professional life, limiting the gains from the activity for the scientific area, with admission to graduate studies and publication of articles. Methodologically, the study has a quantitative nature, where data were collected from multiple sources. Socio-educational, academic and participation information in UR were collected from the UFPR's own bases - Integrated Teaching System (SEI), Contests Center (NC) and Scientific and Technological Initiation System (SICT). For graduate scientific information and publications, data were collected from the Curriculum Lattes platform, while professional data were selected from the Annual Social Information List (RAIS). To achieve the objective of the study, bivariate statistical techniques and multiple correspondence analysis were used in the 37,516 undergraduates of UFPR - 8.133 with UR, 29.383 without UR - in order to identify the characteristics and differences between the UR students gruoup vs No UR students grouo, and validate the research protocol and thesis presented. The results showed that: i) in the socio-educational scope, graduates who participated in the IC were slightly younger; predominantly female; showed less interest in participating in full-time professional activities during the course; and showed better performance in the entrance exam; there was no difference for quota or race variables; ii) in the academic sphere, graduates with UR had a higher course load; were associated with morning shift courses; and figured more intensely in the areas of Applied Social Sciences and Health Sciences; and also had a higher academic performance index; iii) in the scientific scope, UR graduates showed greates fowarding to stricto sensu and lato sensu graduate courses, and higher averages for all variables of analyzed publications, both during graduation and after this period; iv) in the professional variables, there was greater employability over the years for graduates without UR; when observing the employability for teaching in higher education, the percentages were higher for UR students; in all variables involving remuneration, there was no pattern that could place a group in a favorable way or even prominently in relation to the other. The results strengthen the idea that the benefits provided by the UR are mainly for the scientific area of the graduating st dents, with emphasis on the referral to postgraduate studies and publications