Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.

Women-led Community Development Organizations (CDOs) in Miami-Dade County: A Model of Community Development Efforts Impacting the Economic Security of Women

Recent studies on the economic status of women in Miami-Dade County (MDC) reveal an alarming rate of economic insecurity and significant obstacles for women to achieve economic security. Consistent barriers to women’s economic security affect not only the health and wellbeing of women and their families, but also economic prospects for the community. A key study reveals in Miami-Dade County, “Thirty-nine percent of single female-headed families with at least one child are living at or below the federal poverty level” and “over half of working women do not earn adequate income to cover their basic necessities” (Brion 2009, 1). Moreover, conventional measures of poverty do not adequately capture women’s struggles to support themselves and their families, nor do they document the numbers of women seeking basic self-sufficiency. Even though there is lack of accurate data on women in the county, which is a critical problem, there is also a dearth of social science research on existing efforts to enhance women’s economic security in Miami-Dade County. My research contributes to closing the information gap by examining the characteristics and strategies of women-led community development organizations (CDOs) in MDC, working to address women’s economic insecurity. The research is informed by a framework developed by Marilyn Gittell, who pioneered an approach to study women-led CDOs in the United States. On the basis of research in nine U.S. cities, she concluded that women-led groups increased community participation and “by creating community networks and civic action, they represent a model for community development efforts” (Gittell, et al. 2000, 123). My study documents the strategies and networks of women-led CDOs in MDC that prioritize women’s economic security. Their strategies are especially important during these times of economic recession and government reductions in funding towards social services. The focus of the research is women-led CDOs that work to improve social services access, economic opportunity, civic participation and capacity, and women’s rights. Although many women-led CDOs prioritize building social infrastructures that promote change, inequalities in economic and political status for women without economic security remain a challenge (Young 2004). My research supports previous studies by Gittell, et al., finding that women-led CDOs in Miami-Dade County have key characteristics of a model of community development efforts that use networking and collaboration to strengthen their broad, integrated approach. The resulting community partnerships, coupled with participation by constituents in the development process, build a foundation to influence policy decisions for social change. In addition, my findings show that women-led CDOs in Miami-Dade County have a major focus on alleviating poverty and economic insecurity, particularly that of women. Finally, it was found that a majority of the five organizations network transnationally, using lessons learned to inform their work of expanding the agency of their constituents and placing the economic empowerment of women as central in the process of family and community development.

What Influences Information Security Behavior? A Study with Brazilian Users

The popularization of software to mitigate Information Security threats can produce an exaggerated notion about its full effectiveness in the elimination of any threat. This situation can result reckless users behavior, increasing vulnerability. Based on behavioral theories, a theoretical model and hypotheses were developed to understand the extent to which human perception of threat, stress, control and disgruntlement can induce responsible behavior. A self-administered questionnaire was created and validated. The data were collected in Brazil, and complementary results regarding similar studies conducted in USA were found. The results show that there is influence of information security orientations provided by organizations in the perception about severity of the threat. The relationship between threat, effort, control and disgruntlement, and the responsible behavior towards information security was verified through linear regression. The contributions also involve relatively new concepts in the field and a new research instrument.

Secure and Privacy-aware Data Collection and Processing in Mobile Health Systems

Healthcare systems have assimilated information and communication technologies in order to improve the quality of healthcare and patient's experience at reduced costs. The increasing digitalization of people's health information raises however new threats regarding information security and privacy. Accidental or deliberate data breaches of health data may lead to societal pressures, embarrassment and discrimination. Information security and privacy are paramount to achieve high quality healthcare services, and further, to not harm individuals when providing care. With that in mind, we give special attention to the category of Mobile Health (mHealth) systems. That is, the use of mobile devices (e.g., mobile phones, sensors, PDAs) to support medical and public health. Such systems, have been particularly successful in developing countries, taking advantage of the flourishing mobile market and the need to expand the coverage of primary healthcare programs. Many mHealth initiatives, however, fail to address security and privacy issues. This, coupled with the lack of specific legislation for privacy and data protection in these countries, increases the risk of harm to individuals. The overall objective of this thesis is to enhance knowledge regarding the design of security and privacy technologies for mHealth systems. In particular, we deal with mHealth Data Collection Systems (MDCSs), which consists of mobile devices for collecting and reporting health-related data, replacing paper-based approaches for health surveys and surveillance. This thesis consists of publications contributing to mHealth security and privacy in various ways: with a comprehensive literature review about mHealth in Brazil; with the design of a security framework for MDCSs (SecourHealth); with the design of a MDCS (GeoHealth); with the design of Privacy Impact Assessment template for MDCSs; and with the study of ontology-based obfuscation and anonymisation functions for health data.

Big data, smart homes and ambient assisted living

Objectives: To discuss how current research in the area of smart homes and ambient assisted living will be influenced by the use of big data. Methods: A scoping review of literature published in scientific journals and conference proceedings was performed, focusing on smart homes, ambient assisted living and big data over the years 2011-2014. Results: The health and social care market has lagged behind other markets when it comes to the introduction of innovative IT solutions and the market faces a number of challenges as the use of big data will increase. First, there is a need for a sustainable and trustful information chain where the needed information can be transferred from all producers to all consumers in a structured way. Second, there is a need for big data strategies and policies to manage the new situation where information is handled and transferred independently of the place of the expertise. Finally, there is a possibility to develop new and innovative business models for a market that supports cloud computing, social media, crowdsourcing etc. Conclusions: The interdisciplinary area of big data, smart homes and ambient assisted living is no longer only of interest for IT developers, it is also of interest for decision makers as customers make more informed choices among today's services. In the future it will be of importance to make information usable for managers and improve decision making, tailor smart home services based on big data, develop new business models, increase competition and identify policies to ensure privacy, security and liability.

B-1 Monthly Report of Medical Services Provided under Title XIX of the Social Security Act, November 2016

B-1 Medicaid Reports -- The monthly Medicaid series of eight reports provide summaries of Medicaid eligibles, recipients served, and total payments by county, category of service, and aid category. These reports may also be known as the B-1 Reports. These reports are each available as a PDF for printing or as a CSV file for data analysis. Report Report name IAMM1800-R001--Medically Needy by County - No Spenddown and With Spenddown; IAMM1800-R002--Total Medically Needy, All Other Medicaid, and Grand Total by County; IAMM2200-R002--Monthly Expenditures by Category of Service; IAMM2200-R003--Fiscal YTD Expenditures by Category of Service; IAMM3800-R001--ICF & ICF-MR Vendor Payments by County; IAMM4400-R001--Monthly Expenditures by Eligibility Program; IAMM4400-R002--Monthly Expenditures by Category of Service by Program; IAMM4600-R002--Elderly Waiver Summary by County.

B-1 Monthly Report of Medical Services Provided under Title XIX of the Social Security Act, November 2016

B-1 Medicaid Reports -- The monthly Medicaid series of eight reports provide summaries of Medicaid eligibles, recipients served, and total payments by county, category of service, and aid category. These reports may also be known as the B-1 Reports. These reports are each available as a PDF for printing or as a CSV file for data analysis. Report Report name IAMM1800-R001--Medically Needy by County - No Spenddown and With Spenddown; IAMM1800-R002--Total Medically Needy, All Other Medicaid, and Grand Total by County; IAMM2200-R002--Monthly Expenditures by Category of Service; IAMM2200-R003--Fiscal YTD Expenditures by Category of Service; IAMM3800-R001--ICF & ICF-MR Vendor Payments by County; IAMM4400-R001--Monthly Expenditures by Eligibility Program; IAMM4400-R002--Monthly Expenditures by Category of Service by Program; IAMM4600-R002--Elderly Waiver Summary by County.

B-1 Monthly Report of Medical Services Provided under Title XIX of the Social Security Act, December 2016

B-1 Medicaid Reports -- The monthly Medicaid series of eight reports provide summaries of Medicaid eligibles, recipients served, and total payments by county, category of service, and aid category. These reports may also be known as the B-1 Reports. These reports are each available as a PDF for printing or as a CSV file for data analysis. Report Report name IAMM1800-R001--Medically Needy by County - No Spenddown and With Spenddown; IAMM1800-R002--Total Medically Needy, All Other Medicaid, and Grand Total by County; IAMM2200-R002--Monthly Expenditures by Category of Service; IAMM2200-R003--Fiscal YTD Expenditures by Category of Service; IAMM3800-R001--ICF & ICF-MR Vendor Payments by County; IAMM4400-R001--Monthly Expenditures by Eligibility Program; IAMM4400-R002--Monthly Expenditures by Category of Service by Program; IAMM4600-R002--Elderly Waiver Summary by County.

Assessing mackerel scad, Decapterus macarellus, in Cape Verde: using a Bayesian approach to biomass dynamic modelling in a data-limited situation

The fisheries for mackerel scad, Decapterus macarellus, are particularly important in Cape Verde, constituting almost 40% of total catches at the peak of the fishery in 1997 and 1998 ( 3700 tonnes). Catches have been stable at a much lower level of about 2 100 tonnes in recent years. Given the importance of mackerel scad in terms of catch weight and local food security, there is an urgent need for updated assessment. Stock assessment was carried out using a Bayesian approach to biomass dynamic modelling. In order to tackle the problem of a non-informative CPUE series, the intrinsic rate of increase, r, was estimated separately, and the ratio B-0/X, initial biomass relative to carrying capacity, was assumed based on available information. The results indicated that the current level of fishing is sustainable. The probability of collapse is low, particularly in the short-term, and it is likely that biomass may increase further above B-msy, indicating a healthy stock level. It would appear that it is relatively safe to increase catches even up to 4000 tonnes. However, the marginal posterior of r was almost identical to the prior, indicating that there is relatively low information content in CPUE. This was also the case in relation to B-0/X There have been substantial increases in fishing efficiency, which have not been adequately captured by the measure used for effort (days or trips), implying that the results may be overly optimistic and should be considered preliminary. (c) 2006 Elsevier B.V. All rights reserved.

Data protection by design in the e-health care sector: theoretical and applied perspectives

In the digital age, e-health technologies play a pivotal role in the processing of medical information. As personal health data represents sensitive information concerning a data subject, enhancing data protection and security of systems and practices has become a primary concern. In recent years, there has been an increasing interest in the concept of Privacy by Design, which aims at developing a product or a service in a way that it supports privacy principles and rules. In the EU, Article 25 of the General Data Protection Regulation provides a binding obligation of implementing Data Protection by Design technical and organisational measures. This thesis explores how an e-health system could be developed and how data processing activities could be carried out to apply data protection principles and requirements from the design stage. The research attempts to bridge the gap between the legal and technical disciplines on DPbD by providing a set of guidelines for the implementation of the principle. The work is based on literature review, legal and comparative analysis, and investigation of the existing technical solutions and engineering methodologies. The work can be differentiated by theoretical and applied perspectives. First, it critically conducts a legal analysis on the principle of PbD and it studies the DPbD legal obligation and the related provisions. Later, the research contextualises the rule in the health care field by investigating the applicable legal framework for personal health data processing. Moreover, the research focuses on the US legal system by conducting a comparative analysis. Adopting an applied perspective, the research investigates the existing technical methodologies and tools to design data protection and it proposes a set of comprehensive DPbD organisational and technical guidelines for a crucial case study, that is an Electronic Health Record system.

Ray-tracing assessment of the robustness of Physical Layer Security key generation protocol

Nowadays, information security is a very important topic. In particular, wireless networks are experiencing an ongoing widespread diffusion, also thanks the increasing number of Internet Of Things devices, which generate and transmit a lot of data: protecting wireless communications is of fundamental importance, possibly through an easy but secure method. Physical Layer Security is an umbrella of techniques that leverages the characteristic of the wireless channel to generate security for the transmission. In particular, the Physical Layer based-Key generation aims at allowing two users to generate a random symmetric keys in an autonomous way, hence without the aid of a trusted third entity. Physical Layer based-Key generation relies on observations of the wireless channel, from which harvesting entropy: however, an attacker might possesses a channel simulator, for example a Ray Tracing simulator, to replicate the channel between the legitimate users, in order to guess the secret key and break the security of the communication. This thesis work is focused on the possibility to carry out a so called Ray Tracing attack: the method utilized for the assessment consist of a set of channel measurements, in different channel conditions, that are then compared with the simulated channel from the ray tracing, to compute the mutual information between the measurements and simulations. Furthermore, it is also presented the possibility of using the Ray Tracing as a tool to evaluate the impact of channel parameters (e.g. the bandwidth or the directivity of the antenna) on the Physical Layer based-Key generation. The measurements have been carried out at the Barkhausen Institut gGmbH in Dresden (GE), in the framework of the existing cooperation agreement between BI and the Dept. of Electrical, Electronics and Information Engineering "G. Marconi" (DEI) at the University of Bologna.

The environmental DNA in the risk assessment and decision making processes for the invasive species management in agri-food sector, hydraulic security and biodiversity conservation

The use of environmental DNA (eDNA) analysis as a monitoring tool is becoming more and more widespread. The eDNA metabarcoding methods allow rapid community assessments of different target taxa. This work is focused on the validation of the environmental DNA metabarcoding protocol for biodiversity assessment of freshwater habitats. Scolo Dosolo was chosen as study area and three sampling points were defined for traditional and eDNA analyses. The gutter is a 205 m long anthropic canal located in Sala Bolognese (Bologna, Italy). Fish community and freshwater invertebrate metazoans were the target groups for the analysis. After a preliminary study in summer 2019, 2020 was devoted to the sampling campaign with winter (January), spring (May), summer (July) and autumn (October) surveys. Alongside with the water samplings for the eDNA study, also traditional fish surveys using the electrofishing technique were performed to assess fish community composition; census on invertebrates was performed using an entomological net and a surber sampler. After in silico analysis, the MiFish primer set amplifying a fragment of the 12s rRNA gene was selected for bony fishes. For invertebrates the FWHF2 + FWHR2N primer combination, that amplifies a region of the mitochondrial coi gene, was chosen. Raw reads were analyzed through a bioinformatic pipeline based on OBITools metabarcoding programs package and QIIME2. The OBITools pipeline retrieved seven fish taxa and 54 invertebrate taxa belonging to six different phyla, while QIIME2 recovered eight fish taxa and 45 invertebrate taxa belonging to the same six phyla as the OBITools pipeline. The metabarcoding results were then compared with the traditional surveys data and bibliographic records. Overall, the validated protocol provides a reliable picture of the biodiversity of the study area and an efficient support to the traditional methods.

Small Area Estimation of Economic Security

The objective of this thesis is the small area estimation of an economic security indicator. Economic security is a complex concept that carries a variety of meanings. In the literature there is no a formal unambiguous definition for economic security and in this work we refer to the definition recently provided for its opposite, economic insecurity, as the “anxiety produced by the possible exposure to adverse economic events and by the anticipation of the difficulty to recover from them” (Bossert and D’Ambrosio, 2013). In the last decade interest for economic insecurity/security has grown constantly, especially since the financial crisis of 2008, but even more in the last year after the economic consequences due to the Covid-19 pandemic. In this research, economic security is measures through a longitudinal indicator that takes into account the income levels of Italian households, from 2014 to 2016. The target areas are groups of Italian provinces, for which the indicator is estimated using longitudinal data taken from EU-SILC survey. We notice that the sample size is too low to obtain reliable estimates for our target areas. Therefore we resort to some Small Area Estimation strategies to improve the reliability of the results. In particular we consider small area models specified at area level. Besides the basic Fay-Herriot area-level model, we propose to consider some longitudinal extensions, including time-specific random effects following an autoregressive processes of order 1 (AR1) and a moving average of order 1 (MA1). We found that all the small area models used show a significant efficiency gain, especially MA1 model.

Security enhancements and flaws of emerging communication technologies

The multi-faced evolution of network technologies ranges from big data centers to specialized network infrastructures and protocols for mission-critical operations. For instance, technologies such as Software Defined Networking (SDN) revolutionized the world of static configuration of the network - i.e., by removing the distributed and proprietary configuration of the switched networks - centralizing the control plane. While this disruptive approach is interesting from different points of view, it can introduce new unforeseen vulnerabilities classes. One topic of particular interest in the last years is industrial network security, an interest which started to rise in 2016 with the introduction of the Industry 4.0 (I4.0) movement. Networks that were basically isolated by design are now connected to the internet to collect, archive, and analyze data. While this approach got a lot of momentum due to the predictive maintenance capabilities, these network technologies can be exploited in various ways from a cybersecurity perspective. Some of these technologies lack security measures and can introduce new families of vulnerabilities. On the other side, these networks can be used to enable accurate monitoring, formal verification, or defenses that were not practical before. This thesis explores these two fields: by introducing monitoring, protections, and detection mechanisms where the new network technologies make it feasible; and by demonstrating attacks on practical scenarios related to emerging network infrastructures not protected sufficiently. The goal of this thesis is to highlight this lack of protection in terms of attacks on and possible defenses enabled by emerging technologies. We will pursue this goal by analyzing the aforementioned technologies and by presenting three years of contribution to this field. In conclusion, we will recapitulate the research questions and give answers to them.

Edge and Big Data technologies for Industry 4.0 to create an integrated pre-sale and after-sale environment

The fourth industrial revolution, also known as Industry 4.0, has rapidly gained traction in businesses across Europe and the world, becoming a central theme in small, medium, and large enterprises alike. This new paradigm shifts the focus from locally-based and barely automated firms to a globally interconnected industrial sector, stimulating economic growth and productivity, and supporting the upskilling and reskilling of employees. However, despite the maturity and scalability of information and cloud technologies, the support systems already present in the machine field are often outdated and lack the necessary security, access control, and advanced communication capabilities. This dissertation proposes architectures and technologies designed to bridge the gap between Operational and Information Technology, in a manner that is non-disruptive, efficient, and scalable. The proposal presents cloud-enabled data-gathering architectures that make use of the newest IT and networking technologies to achieve the desired quality of service and non-functional properties. By harnessing industrial and business data, processes can be optimized even before product sale, while the integrated environment enhances data exchange for post-sale support. The architectures have been tested and have shown encouraging performance results, providing a promising solution for companies looking to embrace Industry 4.0, enhance their operational capabilities, and prepare themselves for the upcoming fifth human-centric revolution.