146 research outputs found
A strategic turnaround model for distressed properties
The importance of commercial real estate is clearly shown by the role it plays, worldwide, in the sustainability of economic activities, with a substantial global impact when measured in monetary terms. This study responds to an important gap in the built environment and turnaround literature relating to the likelihood of a successful distressed commercial property financial recovery. The present research effort addressed the absence of empirical evidence by identifying a number of important factors that influence the likelihood of a successful distressed, commercial property financial recovery. Once the important factors that increase the likelihood of recovery have been determined, the results can be used as a basis for turnaround strategies concerning property investors who invest in distressed opportunities. A theoretical turnaround model concerning properties in distress, would be of interest to âopportunistic investingâ yield-hungry investors targeting real estate transactions involving âturnaroundâ potential. Against this background, the main research problem investigated in the present research effort was as follows: Determine the important factors that would increase the likelihood of a successful distressed commercial property financial recovery. A proposed theoretical model was constructed and empirically tested through a questionnaire distributed physically and electronically to a sample of real estate practitioners from across the globe, and who had all been involved, directly or indirectly, with reviving distressed properties. An explanation was provided to respondents of how the questionnaire was developed and how it would be administered. The demographic information pertaining to the 391 respondents was analysed and summarised. The statistical analysis performed to ensure the validity and reliability of the results, was explained to respondents, together with a detailed description of the covariance structural equation modelling method used to verify the proposed theoretical conceptual model. vi The independent variables of the present research effort comprised; Obsolescence Identification, Capital Improvements Feasibility, Tenant Mix, Triple Net Leases, Concessions, Property Management, Contracts, Business Analysis, Debt Renegotiation, Cost-Cutting, Market Analysis, Strategic Planning and Demography, while the dependent variable was The Perceived Likelihood of a Distressed Commercial Property Financial Recovery. After analysis of the findings, a revised model was then proposed and assessed. Both validity and reliability were assessed and resulted in the following factors that potentially influence the dependent variables; Strategy, Concessions, Tenant Mix, Debt Restructuring, Demography, Analyse Alternatives, Capital Improvements Feasibility, Property Management and Net Leases while, after analysis, the dependent variable was replaced by two dependent variables; The Likelihood of a Distressed Property Turnaround and The Likelihood of a Distressed Property Financial Recovery. The results showed that Strategy (comprising of items from Strategic Planning, Business Analysis, Obsolescence Identification and Property Management) and Concessions (comprising of items from Concessions and Triple Net Leases) had a positive influence on both the dependent variables. Property Management (comprising of items from Business Analysis, Property Management, Capital Improvements Feasibility and Tenant Mix) had a positive influence on Financial Turnaround variable while Capital Improvements Feasibility (comprising of items from Capital Improvements Feasibility, Obsolescence Identification and Property Management) had a negative influence on both. Demography (comprising of items only from Demography) had a negative influence on the Financial Recovery variable. The balance of the relationships were depicted as non-significant. The present research effort presents important actions that can be used to influence the turnaround and recovery of distressed real estate. The literature had indicated reasons to recover distressed properties as having wide-ranging economic consequences for the broader communities and the countries in which they reside. The turnaround of distressed properties will not only present financial rewards for opportunistic investors but will have positive effects on the greater community and economy and, thus, social and economic stability. Vii With the emergence of the COVID-19 pandemic crisis, issues with climate change and sustainability, global demographic shifts, changing user requirements, shifts in technology, the threat of obsolescence, urbanisation, globalisation, geo-political tensions, shifting global order, new trends and different generational expectations, it is becoming more apparent that the threat of distressed, abandoned and derelict properties is here to stay, and which will present future opportunities for turnaround, distressed property owners, as well as future worries for urban authorities and municipalities dealing with urban decay. The study concluded with an examination of the perceived limitations of the study as well as presenting a comprehensive range of suggestions for further research.Thesis (PhD) -- Faculty of Engineering, Built Environment and Information Technology, School of the built Environment, 202
Design and analysis of miniaturized substrate integrated waveguide reconfigurable filters for mm-wave applications.
Doctoral Degree. University of KwaZulu-Natal, Durban.Microwave filters are an integral part of communication systems. With the advent of new technologies, microwave devices, such as filters, need to have superior performance in terms of power handling, selectivity, size, insertion loss etc. During the past decade, many applications have been added to the communication networks, resulting in communication systems having to operate at high frequencies in the region of THz to achieve the stringent bandwidth requirements. To achieve the requirements of the modern communication system, tunability and reconfigurability have become fundamental requirements to reduce the footprint of communication devices. However, the communication systems that are more prevalent such as planar circuits have either a large footprint or are not able to handle large amounts of power due to radiation leakage. In this thesis, Substrate Integrated Waveguide (SIW) technology has been employed.
The SIW has the same properties as the conventional rectangular waveguide; hence it benefits from the high quality (Q) factor and can handle large powers with small radiation loss. The Half-mode (HMSIW), Quarter-mode (QMSIW), and Eighth-mode (EMSIW) cavity resonators have been designed and used for the miniaturization of the microwave filters. The coupling matrix method was used to implement a filter that uses cross-coupled EMSIW and HMSIW cavity resonators to improve the selectivity of the filter. Balanced circuit techniques have been used to design the circuits that preserve communication systems integrity whereby the Common Mode (CM) signal was suppressed using Deformed Ground Structure (DGS) and a center conductor patch with meandered line. For the designed dual-band filter, the common mode signal was suppressed to -90 dB and - 40 dB for the first and second passband, respectively. The insertion loss observed is 2.8 dB and 1.6 dB for the first and second passband, respectively.
For tunability of the filter, a dual-band filter utilizing triangular HMSIW resonators has been designed and reconfigurability is achieved by perturbing the substrate permittivity by dielectric rods. The dielectric rodsâ permittivity was changed to achieve tunability in the first instance, and then the rodsâ diameter changed in the second instance. For the lowerband, frequency is tunable from 8.1 GHz to 9.15 GHz, while the upper band is tuned from 14.61 GHz to 16.10 GHz. A second order SIW filter with a two layer substrate was then designed to operate in the THz region. For reconfigurability, Graphene was sandwiched between the Silicon Di-Oxide substrate and the top gold plate of the filter, and the chemical potential of Graphene was then varied by applying a dc bias voltage. With a change in dc voltage the chemical potential of Graphene changes accordingly. From the results, a chemical potential change of 0.1 eV to 0.6 eV brings about a frequency change from 1.289 THz to 1.297 THz
Artificial Intelligence-enabled Automation for Compliance Checking against GDPR
Requirements engineering (RE) is concerned with eliciting legal requirements from applicable regulations to enable developing legally compliant software. Current software systems rely heavily on data, some of which can be confidential, personal, or sensitive. To address the growing concerns about data protection and privacy, the general data protection regulation (GDPR) has been introduced in the European Union (EU). Organizations, whether based in the EU or not, must comply with GDPR as long as they collect or process personal data of EU residents. Breaching GDPR can be charged with large fines reaching up to up to billions of euros. Privacy policies (PPs) and data processing agreements (DPAs) are documents regulated by GDPR to ensure, among other things, secure collection and processing of personal data. Such regulated documents can be used to elicit legal requirements that are inline with the organizationsâ data protection policies. As a prerequisite to elicit a complete set of legal requirements, however, these documents must be compliant with GDPR. Checking the compliance of regulated documents entirely manually is a laborious and error-prone task. As we elaborate below, this dissertation investigates utilizing artificial intelligence (AI) technologies to provide automated support for compliance checking against GDPR.
âą AI-enabled Automation for Compliance Checking of PPs: PPs are technical documents stating the multiple privacy-related requirements that a system should satisfy in order to help individuals make informed decisions about sharing their personal data. We devise an automated solution that leverages natural language processing (NLP) and machine learning (ML), two sub-fields of AI, for checking the compliance of PPs against the applicable provisions in GDPR. Specifically, we create a comprehensive conceptual model capturing all information types pertinent to PPs and we further define a set of compliance criteria for the automated compliance checking of PPs.
âą NLP-based Automation for Compliance Checking of DPAs: DPAs are legally binding agreements between different organizations involved in the collection and processing of personal data to ensure that personal data remains protected. Using NLP semantic analysis technologies, we develop an automated solution that checks at phrasal-level the compliance of DPAs against GDPR. Our solution is able to provide not only a compliance assessment, but also detailed recommendations about avoiding GDPR violations.
âą ML-enabled Automation for Compliance Checking of DPAs: To understand how different representations of GDPR requirements and different enabling technologies fare against one another, we develop an automated solution that utilizes a combination of conceptual modeling and ML. We further empirically compare the resulting solution with our previously proposed solution, which uses natural language to represent GDPR requirements and leverages rules alongside NLP semantic analysis for the automated support
Challenges and perspectives of hate speech research
This book is the result of a conference that could not take place. It is a collection of 26 texts that address and discuss the latest developments in international hate speech research from a wide range of disciplinary perspectives. This includes case studies from Brazil, Lebanon, Poland, Nigeria, and India, theoretical introductions to the concepts of hate speech, dangerous speech, incivility, toxicity, extreme speech, and dark participation, as well as reflections on methodological challenges such as scraping, annotation, datafication, implicity, explainability, and machine learning. As such, it provides a much-needed forum for cross-national and cross-disciplinary conversations in what is currently a very vibrant field of research
Disclosure of suicidal drivers on social media: a natural language processing and thematic analysis approach
It is common for people to search for health information on the internet, share their health issues through social media, and ask for advice from people in online communities. Some people reported feeling more comfortable sharing their psychological stress online and anonymously asking for advice from people. As such, people disclose not only their suicide risk but also their suicidal risk-associated drivers (e.g., suicide ideation, relational stress, financial crisis). This study aims to identify suicidal drivers from narratives extracted from social media, synthesize findings and suicide theories, and provide insights into future suicide prevention policies and practices.
This research gathered and analyzed 128,587 posts written by 76,547 people worldwide. The posts were written in English from January 2021 to December 2022 on the r/SuicideWatch of Reddit. Natural Language Processing and topic modeling, specifically Latent Dirichlet Allocation (LDA), were used to identify clusters of posts based on similarities and differences between posts. Thematic analysis was used to identify suicidal drivers across clusters of posts. The web crawler developed by Brandwatch was used in data collection, and Python was used for all analyses.Â
Six theme clusters of posts were identified. The first theme was Disclosure of Repetitive Suicide Ideation (i.e., âI want to die. I want to die, I want to dieâŠ(repeated)â), and 36.4% of posts had this theme. The second theme was Disclosure of Relational Stress (i.e., âI donât have any friendsâ), and 31.9% of posts had this theme. The third theme was Disclosure of Suicide Attempts and Negative Healthcare Experiences (i.e., âIâve had a suicide attempt beforeâ, âThe nurses ignored meâ), and 9.9% of posts had this theme. The fourth theme was Disclosure of Abuse (i.e., âHe would beat me black and blueâ), and 8.8% of posts had this theme. The fifth theme was Disclosure of Contextual Stress, including finance and legal matters (i.e., âevery moment was a living fear of the debt collector knocking on the doorâ), and 7.2% of posts had this theme. The last theme was Philosophical and Informative Discussions around suicide (i.e., âAfter death, the physical begins to deteriorate and life/energy is simply moved to another beingâ), and 5.8% of posts had this theme.
Understanding different suicidal drivers is an essential component in designing individualized intervention plans for people at suicide risk. The current research identified the idiosyncrasies in the suicide drivers people talked about when disclosing their suicidality. Furthermore, the findings from this studyâs data-inspired and exploratory approach provided additional evidence supporting existing suicide theories and frameworks. This research has the potential to lay the groundwork for designing suicide intervention strategies that target individualsâ self-disclosures of their struggles online
Geographic information extraction from texts
A large volume of unstructured texts, containing valuable geographic information, is available online. This information â provided implicitly or explicitly â is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction
Sensing the Cultural Significance with AI for Social Inclusion
Social Inclusion has been growing as a goal in heritage management. Whereas the 2011 UNESCO Recommendation on the Historic Urban Landscape (HUL) called for tools of knowledge documentation, social media already functions as a platform for online communities to actively involve themselves in heritage-related discussions. Such discussions happen both in âbaseline scenariosâ when people calmly share their experiences about the cities they live in or travel to, and in âactivated scenariosâ when radical events trigger their emotions. To organize, process, and analyse the massive unstructured multi-modal (mainly images and texts) user-generated data from social media efficiently and systematically, Artificial Intelligence (AI) is shown to be indispensable. This thesis explores the use of AI in a methodological framework to include the contribution of a larger and more diverse group of participants with user-generated data. It is an interdisciplinary study integrating methods and knowledge from heritage studies, computer science, social sciences, network science, and spatial analysis. AI models were applied, nurtured, and tested, helping to analyse the massive information content to derive the knowledge of cultural significance perceived by online communities. The framework was tested in case study cities including Venice, Paris, Suzhou, Amsterdam, and Rome for the baseline and/or activated scenarios. The AI-based methodological framework proposed in this thesis is shown to be able to collect information in cities and map the knowledge of the communities about cultural significance, fulfilling the expectation and requirement of HUL, useful and informative for future socially inclusive heritage management processes
Jornadas Nacionales de InvestigaciĂłn en Ciberseguridad: actas de las VIII Jornadas Nacionales de InvestigaciĂłn en ciberseguridad: Vigo, 21 a 23 de junio de 2023
Jornadas Nacionales de InvestigaciĂłn en Ciberseguridad (8ÂȘ. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernizaciĂłn tecnolĂłxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida
LIPIcs, Volume 274, ESA 2023, Complete Volume
LIPIcs, Volume 274, ESA 2023, Complete Volum
A strategic turnaround model for distressed properties
The importance of commercial real estate is clearly shown by the role it plays, worldwide, in the sustainability of economic activities, with a substantial global impact when measured in monetary terms. This study responds to an important gap in the built environment and turnaround literature relating to the likelihood of a successful distressed commercial property financial recovery. The present research effort addressed the absence of empirical evidence by identifying a number of important factors that influence the likelihood of a successful distressed, commercial property financial recovery. Once the important factors that increase the likelihood of recovery have been determined, the results can be used as a basis for turnaround strategies concerning property investors who invest in distressed opportunities. A theoretical turnaround model concerning properties in distress, would be of interest to âopportunistic investingâ yield-hungry investors targeting real estate transactions involving âturnaroundâ potential. Against this background, the main research problem investigated in the present research effort was as follows: Determine the important factors that would increase the likelihood of a successful distressed commercial property financial recovery. A proposed theoretical model was constructed and empirically tested through a questionnaire distributed physically and electronically to a sample of real estate practitioners from across the globe, and who had all been involved, directly or indirectly, with reviving distressed properties. An explanation was provided to respondents of how the questionnaire was developed and how it would be administered. The demographic information pertaining to the 391 respondents was analysed and summarised. The statistical analysis performed to ensure the validity and reliability of the results, was explained to respondents, together with a detailed description of the covariance structural equation modelling method used to verify the proposed theoretical conceptual model. vi The independent variables of the present research effort comprised; Obsolescence Identification, Capital Improvements Feasibility, Tenant Mix, Triple Net Leases, Concessions, Property Management, Contracts, Business Analysis, Debt Renegotiation, Cost-Cutting, Market Analysis, Strategic Planning and Demography, while the dependent variable was The Perceived Likelihood of a Distressed Commercial Property Financial Recovery. After analysis of the findings, a revised model was then proposed and assessed. Both validity and reliability were assessed and resulted in the following factors that potentially influence the dependent variables; Strategy, Concessions, Tenant Mix, Debt Restructuring, Demography, Analyse Alternatives, Capital Improvements Feasibility, Property Management and Net Leases while, after analysis, the dependent variable was replaced by two dependent variables; The Likelihood of a Distressed Property Turnaround and The Likelihood of a Distressed Property Financial Recovery. The results showed that Strategy (comprising of items from Strategic Planning, Business Analysis, Obsolescence Identification and Property Management) and Concessions (comprising of items from Concessions and Triple Net Leases) had a positive influence on both the dependent variables. Property Management (comprising of items from Business Analysis, Property Management, Capital Improvements Feasibility and Tenant Mix) had a positive influence on Financial Turnaround variable while Capital Improvements Feasibility (comprising of items from Capital Improvements Feasibility, Obsolescence Identification and Property Management) had a negative influence on both. Demography (comprising of items only from Demography) had a negative influence on the Financial Recovery variable. The balance of the relationships were depicted as non-significant. The present research effort presents important actions that can be used to influence the turnaround and recovery of distressed real estate. The literature had indicated reasons to recover distressed properties as having wide-ranging economic consequences for the broader communities and the countries in which they reside. The turnaround of distressed properties will not only present financial rewards for opportunistic investors but will have positive effects on the greater community and economy and, thus, social and economic stability. Vii With the emergence of the COVID-19 pandemic crisis, issues with climate change and sustainability, global demographic shifts, changing user requirements, shifts in technology, the threat of obsolescence, urbanisation, globalisation, geo-political tensions, shifting global order, new trends and different generational expectations, it is becoming more apparent that the threat of distressed, abandoned and derelict properties is here to stay, and which will present future opportunities for turnaround, distressed property owners, as well as future worries for urban authorities and municipalities dealing with urban decay. The study concluded with an examination of the perceived limitations of the study as well as presenting a comprehensive range of suggestions for further research.Thesis (PhD) -- Faculty of Engineering, Built Environment and Information Technology, School of the built Environment, 202
- âŠ