Application of Fuzzy Cognitive Mapping in Livelihood Vulnerability Analysis

Feedback mechanisms are important in the analysis of vulnerability and resilience of social-ecological systems, as well as in the analysis of livelihoods, but how to evaluate systems with direct feedbacks has been a great challenge. We applied fuzzy cognitive mapping, a tool that allows analysis of both direct and indirect feedbacks and can be used to explore the vulnerabilities of livelihoods to identified hazards. We studied characteristics and drivers of rural livelihoods in the Great Limpopo Transfrontier Conservation Area in southern Africa to assess the vulnerability of inhabitants to the different hazards they face. The process involved four steps: (1) surveys and interviews to identify the major livelihood types; (2) description of specific livelihood types in a system format using fuzzy cognitive maps (FCMs), a semi-quantitative tool that models systems based on people’s knowledge; (3) linking variables and drivers in FCMs by attaching weights; and (4) defining and applying scenarios to visualize the effects of drought and changing park boundaries on cash and household food security. FCMs successfully gave information concerning the nature (increase or decrease) and magnitude by which a livelihood system changed under different scenarios. However, they did not explain the recovery path in relation to time and pattern (e.g., how long it takes for cattle to return to desired numbers after a drought). Using FCMs revealed that issues of policy, such as changing situations at borders, can strongly aggravate effects of climate change such as drought. FCMs revealed hidden knowledge and gave insights that improved the understanding of the complexity of livelihood systems in a way that is better appreciated by stakeholders

Mathematics in Software Reliability and Quality Assurance

This monograph concerns the mathematical aspects of software reliability and quality assurance and consists of 11 technical papers in this emerging area. Included are the latest research results related to formal methods and design, automatic software testing, software verification and validation, coalgebra theory, automata theory, hybrid system and software reliability modeling and assessment

The knowledge, the will and the power : a plan of action to meet the HIV prevention needs of Africans living in England

The Knowledge, The Will and The Power is a statement of what we, the NAHIP Partners, plan to do to prevent HIV transmissions occurring during sexual activity among the diverse population of Africans living in England (Chapter 1). We describe the size and context of Africans living in England (Chapter 2), the size of the HIV epidemic and the number of new infections occurring (Chapter 3), as well as the behaviours and facilitators of new infections (Chapter 4). We then articulate how the NAHIP partners intend to influence future behaviours (Chapter 5). The final three chapters describe what is required in order to meet the HIV prevention needs of individual African people (Chapter 6), of NAHIP partner organisations (Chapter 7) and of those undertaking decisions related to policy, planning and research (Chapter 8)

Advances in model based clustering for the social sciences

This dissertation attempts to gather the main research topics I engaged during my PhD, in collaboration with several national and international researchers. The primary focus of this work is to highlight the power of model based clustering for identifying latent structures in complex data and its usefulness in the social sciences. This methods have become increasingly popular in social science research as they allow for more accurate and nuanced understanding of complex data structures. In the thesis are presented 3 papers that contribute to the development and application of model-based clustering in social science research, covering a range of scenario. The thesis pays particular attention to the practical applications of the treated methods, providing insights that can improve our understanding of complex social phenomena. The first chapter of this dissertation introduces the usefulness of clustering model to deal with the complexity of society, and aware of some of the main issues when analysing socio-economic data. Following this conceptual introduction, the second chapter delves more into the technical aspects of model based clustering and estimation. These first two chapters pave the road for the three developments presented thereafter. The third chapter includes the application of a Mixture of Matrix-Normals classification model to the Migrant Integration Policy Index (MIPEX), that measures and evaluates countries policies toward migrants’ integration over time. The used model is suitable for longitudinal data and allows for the identification of clusters of countries with similar patterns of migrant integration policies over time. The work is published in Alaimo et al. [2021a]. The fourth chapter uses MIPEX data too, but for a single year, and a finite mixtures of multivariate Gaussian is applied to identify groups of countries with a similar level of integration. Then, the relative proportion of immigrants held in prison among clusters is estimated, exploiting Fisher’s noncentral hypergeometric model. The aim of this work is test the existence of an association between countries’ level of integration of immigrants and the proportion of immigrants in prison. The work is currently in referral process. The fifth chapter introduce the work developed during my visiting research period at University of Lyon, Lyon 2. It specify the Bayesian partial membership model for soft clustering of multivariate data, namely when units have fractional membership to multiple groups. The model is specified for count data, and it is applied on the data of the bike sharing company of Washington DC and on the data of Serie A football players. The last chapter summarizes the main points of the dissertation, underlining the most relevant findings, the contributions, and stressing out how clustering models altogether yield a cohesive treatment of socio-economic data

Vulnerability and resilience of competing land-based livelihoods in south eastern Zimbabwe

Key words: vulnerability; resilience; livelihood; drought; Great Limpopo Transfrontier Conservation Area; south eastern Zimbabwe. Vulnerability and resilience have emerged as powerful analytical concepts in the study of socio-ecological systems. In this research these concepts are used to enhance our understanding of heterogeneous rural livelihoods in a semi-arid area on the western border of protected wildlife areas in Zimbabwe’s southeast lowveld. The purpose of this thesis is to develop a methodological approach that helps understanding the vulnerability of rural livelihoods to change and relate this to adaptive mechanisms employed by people to cope with the resulting change. Although most households in the study area keep livestock, practice arable farming, and receive remittances, they differ in terms of their dependency on cattle, cropping, and non-farm and off-farm activities, especially in years of drought. Households most dependent on livestock – the cattle-based livelihood type – generally cope with hazards by selling cattle. Households of the crop-based livelihood type strive to spread the risk of crop failure by cropping across the landscape, ranging from flood plains to uplands on the interfluves. Households of the non-farm livelihood type rely for their survival on paid employment outside the study area, mostly of households’ members working in South Africa. Fuzzy Cognitive Mapping (FCM) was used to assess the vulnerability of the three livelihood types to different hazards. The vulnerability analysis shows that policies relating to the permeability and/or enforcement of protected area boundaries can strongly aggravate the effects of other external influences, such as drought or climate change. To cope with drought-induced fodder shortages, people of cattle-based households have recently started to use Neorautanenia amboensis (Schinz). This tuber shrub, locally known as Zhombwe, is now saving many cattle from death in periods of drought, thus reducing livestock keeping households vulnerability to drought. This thesis shows the anthelmintic properties of Zhombwe; its distribution in the field was quantified. Crop experiments explored adaptive strategies which can be used by the households of the crop-based livelihood type to increase food self-sufficiency. Results show that by making better use of different landscape units in the area food production can be increased, both in good and bad rainfall years. By applying a method like FCM and by analysing quantitatively different options for increasing the resilience of the local households, this thesis shows that it is key to take into account the heterogeneity of rural households in an area, as adaption options differ strongly between them. </p

U.S. Commission on Immigration Reform

The U.S. Commission on Immigration Reform was created by Congress to assess U.S. immigration policy and make recommendations regarding its implementation and effects. Mandated in the Immigration Act of 1990 to submit an interim report in 1994 and a final report in 1997, the Commission has undertaken public hearings, fact-finding missions, and expert consultations to identify the major immigration-related issues facing the United States today.LBJ School of Public Affair

Development of secured algorithm to enhance the privacy and security template of biometric technology

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Mathematical and Computer Science and Engineering of the Nelson Mandela African Institution of Science and TechnologyThe security of information and personal privacy are the growing concerns in today’s human life worldwide. The storage of biometric data in the database has raised the prospect of compromising the database leading to grave risks and misuse of the person’s privacy such as growth in terrorism and identity fraud. When a person’s biometric data stored is revealed, their security and privacy are being compromised. This research described a detailed evaluation on several outbreaks and threats associated with the biometric technology. It analyzed the user’s fear and intimidations to the biometric technology alongside the protection steps for securing the biometric data template in the database. It is known that, when somebody’s biometric data template is compromised from the database that consequently might indicate proof of identity robbery of that person. Mixed method to compute and articulate the results as well as a new tactic of encryption-decryption algorithm with a design pattern of Model View Template (MVT) are used for securing the biometric data template in the database. The model managed information logically, the view indicated the visualization of the data, and the template directed the data migration into pattern object. Factors influencing fear of biometric technology such as an exposer of personal information, improper data transfer, and data misuse are found. Strong knowledge of the ideal technology like the private skills of the biometric technology, data secrecy and perceived helpfulness are established. The fears and attacks along the technology like a counterfeit of documents and brute-force attack are known. The designed algorithm based on the cryptographic module of the Fernet keys instance are utilized. The Fernet keys are combined to generate a multiFernet key, integrated with biometric data to produce two encrypted files (byte and text file). These files are incorporated with Twilio message and firmly stored in the database. The storage database has security measures that guard against an impostor’s attack. The database system can block the attacker from unauthorized access. Thus, significantly increased individual data privacy and integrity

Global Risks 2015, 10th Edition.

The 2015 edition of the Global Risks report completes a decade of highlighting the most significant long-term risks worldwide, drawing on the perspectives of experts and global decision-makers. Over that time, analysis has moved from risk identification to thinking through risk interconnections and the potentially cascading effects that result. Taking this effort one step further, this year's report underscores potential causes as well as solutions to global risks. Not only do we set out a view on 28 global risks in the report's traditional categories (economic, environmental, societal, geopolitical and technological) but also we consider the drivers of those risks in the form of 13 trends. In addition, we have selected initiatives for addressing significant challenges, which we hope will inspire collaboration among business, government and civil society communitie

Integrating openstreetmap data and sentinel-2 Imagery for classifying and monitoring informal settlements

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesThe identification and monitoring of informal settlements in urban areas is an important step in developing and implementing pro-poor urban policies. Understanding when, where and who lives inside informal settlements is critical to efforts to improve their resilience. This study aims at integrating OSM data and sentinel-2 imagery for classifying and monitoring the growth of informal settlements methods to map informal areas in Kampala (Uganda) and Dar es Salaam (Tanzania) and to monitor their growth in Kampala. Three building feature characteristics of size, shape and Distance to nearest Neighbour were derived and used to cluster and classify informal areas using Hotspot Cluster analysis and ML approach on OSM buildings data. The resultant informal regions in Kampala were used with Sentinel-2 image tiles to investigate the spatiotemporal changes in informal areas using Convolutional Neural Networks (CNNs). Results from Optimized Hot Spot Analysis and Random Forest Classification show that Informal regions can be mapped based on building outline characteristics. An accuracy of 90.3% was achieved when an optimally trained CNN was executed on a test set of 2019 satellite image tiles. Predictions of informality from new datasets for the years 2016 and 2017 provided promising results on combining different open source geospatial datasets to identify, classify and monitor informal settlements

Expert Systems for Environmental Screening. An Application in the Lower Mekong Basin

This research report describes MEXSES, a rule-based expert system for environmental impact assessment at a screening level, implemented for the analysis of water resources development projects in the Lower Mekong Basin. The report makes a brief review of environmental impact assessment methods and tools. It discusses expert systems technology, with emphasis on environmental applications. The Lower Mekong Basin and its specific environmental problems, as well as the Mekong Secretariat's environmental policy are examined. Subsequently, the software system is described from a user's perspective, followed by a detailed description of the methodology employed and its implementation. In the final chapter, a number of issues around the successful application of such a system are discussed, including a number of suggested improvements and extensions to the current operational prototype